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Graduate Fellow - AI & Knowledge Mgt.

Ewvl Fa Us8 Oraclecloud Com CX 1 · Aiken, SC, United States; Savannah River National Laboratory · Active · $1,000,000 / year · Oracle Recruiting Cloud / Fusion HCM

Job facts

FieldValue
CompanyEwvl Fa Us8 Oraclecloud Com CX 1
TitleGraduate Fellow - AI & Knowledge Mgt.
Normalized title-
Department / teamEngineering and Science
LocationAiken, SC, United States
Work model-
Employment typeFull Time
Salary$1,000,000 / year
Statusactive
ATS providerOracle Recruiting Cloud / Fusion HCM
Posted / first seen2026-05-27 / 2026-05-31
Changed / last seen2026-06-06 / 2026-06-06

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CompanyEwvl Fa Us8 Oraclecloud Com CX 1
Sourceb6d7720c-a11f-4b08-a6fc-26e55ce739ae
ATS providerOracle Recruiting Cloud / Fusion HCM

Description

Description Savannah River National Laboratory is seeking a highly motivated graduate fellow to advance our AI-driven knowledge management capabilities. This fellowship is focused on building next-generation systems for intelligent information retrieval, knowledge graph construction, and multi-agent AI workflows that support complex scientific workflows. The successful candidate will bring graduate-level research experience in large language models, retrieval-augmented generation (RAG), or knowledge representation, and a passion for applying these techniques to real-world challenges across scientific and engineering domains. Design and implement knowledge management pipelines using large language models (LLMs), retrieval-augmented generation (RAG), and vector databases to enable intelligent information retrieval across large, multi-modal document corpora Develop and evaluate multi-agent AI architectures for automated reasoning, summarization, and decision support Build and maintain knowledge graphs and ontologies to represent complex domain relationships and support semantic search Collaborate with cross-functional research teams to integrate AI knowledge tools into existing scientific workflows and applications Author technical documentation, scientific journal articles, and internal reports communicating methods and findings to both technical and non-technical audiences Participate in code reviews and contribute to a shared, well-maintained research codebase Monitor and evaluate emerging developments in LLMs, agentic AI, and knowledge management frameworks, and assess their applicability to ongoing projects Minimum Qualifications Recent graduate (M.S. or Ph.D.) in Computer Science, Data Science, Information Science, or other scientific and engineering disciplines Strong proficiency in Python, including experience with AI/ML libraries such as PyTorch, Hugging Face Transformers, or LangChain Foundational understanding of large language models, prompt engineering, and retrieval-augmented generation (RAG) Experience with or coursework in natural language processing (NLP) or knowledge representation Ability to clearly document and communicate technical research, including writing reports and presenting findings Ability to obtain and maintain security clearance. US Citizenship is legally required. Preferred Qualifications Research experience or publications related to LLMs, knowledge graphs, information retrieval, or multi-agent systems Hands-on experience building end-to-end RAG pipelines or agentic AI workflows Familiarity with knowledge graph construction, ontology design, or semantic web technologies (RDF, SPARQL, OWL) Experience with vector databases or embedding-based search systems Background in a scientific or national security domain (e.g., environmental science, bioengineering, chemistry) is a plus Experience working in a research or government laboratory environment Responsibilities Design and implement knowledge management pipelines using large language models (LLMs), retrieval-augmented generation (RAG), and vector databases to enable intelligent information retrieval across large, multi-modal document corpora Develop and evaluate multi-agent AI architectures for automated reasoning, summarization, and decision support Build and maintain knowledge graphs and ontologies to represent complex domain relationships and support semantic search Collaborate with cross-functional research teams to integrate AI knowledge tools into existing scientific workflows and applications Author technical documentation, scientific journal articles, and internal reports communicating methods and findings to both technical and non-technical audiences Participate in code reviews and contribute to a shared, well-maintained research codebase Monitor and evaluate emerging developments in LLMs, agentic AI, and knowledge management frameworks, and assess their applicability to ongoing projects Qualifications Minimum Qualifications: Recent graduate (M.S. or Ph.D.) in Computer Science, Data Science, Information Science, or other scientific and engineering disciplines Strong proficiency in Python, including experience with AI/ML libra ries such as PyTorch, Hugging Face Transformers, or LangChain Foundational understanding of large language models, prompt engineering, and retrieval-augmented generation (RAG) Experience with or coursework in natural language processing (NLP) or knowledge representation Ability to clearly document and communicate technical research, including writing reports and presenting findings Self-directed with strong collaboration and interpersonal skills Must be able to obtain and maintain security clearance, for which U.S. Citizenship is legally required. Preferred Qualifications: Research experience or publications related to LLMs, knowledge graphs, information retrieval, or multi-agent systems Hands-on experience building end-to-end RAG pipelines or agentic AI workflows Familiarity with knowledge graph construction, ontology design, or semantic web technologies (RDF, SPARQL, OWL) Experience with vector databases or embedding-based search systems Background in a scientific or national security domain (e.g., environmental science, bioengineering, chemistry) is a plus Experience working in a research or government laboratory environment Organization SRNL’s Environmental & Legacy Management (ELM) Directorate closely collaborates with the Department of Energy (DOE) and site contractors to develop, mature, and apply science and technology needed to resolve environmental challenges and advance legacy management missions. As the lead laboratory for Environmental Management (DOE-EM) and Legacy Management (DOE-LM), SRNL applies our talent and expertise to develop and deploy innovative approaches and technologies to reduce risk, cost, and schedule of environmental cleanup and nuclear material processing. Additionally, ELM is using our competencies to develop new materials and processes for a range of clean energy applications. Company "We put science to work!" Savannah River National Laboratory (SRNL) is a multi-program laboratory applying state of the art science and practical, high-value, cost-effective solutions to complex technical problems to protect the nation. Located at the U.S. Department of Energy’s (DOE) Savannah River Site (SRS) in Aiken SC, the laboratory develops and deploys innovative technologies to address some of the nation’s environmental, energy, and national security challenges. Battelle Savannah River Alliance (BSRA) is constantly assessing trends to provide the best possible benefits to our workforce. We also negotiate cost effective premiums that will meet the needs of our evolving workforce. Some of the *Benefits offered to employees include: *Benefits vary based upon employment status Highly competitive Medical, Dental, and Vision options including HSA options with company provided seed Short- & Long-Term Disability (company paid) Life Insurance Non-Contributary 1X salary (company paid) AD&D Non-contributary 1x salary (company paid) Savings & Investment plan: Qualified Non-Elective Company Contribution of 5% each pay period with immediate vesting Company match 50 cents/dollar up to 8% (5 yrs. vesting in company match) Contributory Life Insurance up to 5x Salary with $1M Cap Contributory AD&D (employee, spouse and children) Paid Time Off Employee Assistance Plan SRNL offers a competitive relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. For more information about our benefits, working here, and living here, visit the “About” tab at www.srnl.doe.gov . BSRA is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected veteran status. BSRA is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. Please email us at [email protected] with any questions regarding the hiring process or to request an accommodation.

Full job record

Job ID4182f0e8edf5b4773e1bf8d1f132144f2913f37e
Org ID27373ce2-efc8-4ffa-b547-2b4c63bdf5c2
Source IDb6d7720c-a11f-4b08-a6fc-26e55ce739ae
Board IDb6d7720c-a11f-4b08-a6fc-26e55ce739ae
Provideroracle_hcm
Provider Job Key2122
TitleGraduate Fellow - AI & Knowledge Mgt.
Normalized Title—
Statusactive
Activeyes
Location TextAiken, SC, United States; Savannah River National Laboratory
DepartmentEngineering and Science
Team—
Employment Typefull_time
Workplace Type—
Remote Policy—
CountryUnited States
RegionSC
CityAiken
Salary RawDescription Savannah River National Laboratory is seeking a highly motivated graduate fellow to advance our AI-driven knowledge management capabilities. This fellowship is focused on building next-generation systems for intelligent information retrieval, knowledge graph construction, and multi-agent AI workflows that support complex scientific workflows. The successful candidate will bring graduate-level research experience in large language models, retrieval-augmented generation (RAG), or knowledge representation, and a passion for applying these techniques to real-world challenges across scientific and engineering domains. Design and implement knowledge management pipelines using large language models (LLMs), retrieval-augmented generation (RAG), and vector databases to enable intelligent information retrieval across large, multi-modal document corpora Develop and evaluate multi-agent AI architectures for automated reasoning, summarization, and decision support Build and maintain knowledge graphs and ontologies to represent complex domain relationships and support semantic search Collaborate with cross-functional research teams to integrate AI knowledge tools into existing scientific workflows and applications Author technical documentation, scientific journal articles, and internal reports communicating methods and findings to both technical and non-technical audiences Participate in code reviews and contribute to a shared, well-maintained research codebase Monitor and evaluate emerging developments in LLMs, agentic AI, and knowledge management frameworks, and assess their applicability to ongoing projects Minimum Qualifications Recent graduate (M.S. or Ph.D.) in Computer Science, Data Science, Information Science, or other scientific and engineering disciplines Strong proficiency in Python, including experience with AI/ML libraries such as PyTorch, Hugging Face Transformers, or LangChain Foundational understanding of large language models, prompt engineering, and retrieval-augmented generation (RAG) Experience with or coursework in natural language processing (NLP) or knowledge representation Ability to clearly document and communicate technical research, including writing reports and presenting findings Ability to obtain and maintain security clearance. US Citizenship is legally required. Preferred Qualifications Research experience or publications related to LLMs, knowledge graphs, information retrieval, or multi-agent systems Hands-on experience building end-to-end RAG pipelines or agentic AI workflows Familiarity with knowledge graph construction, ontology design, or semantic web technologies (RDF, SPARQL, OWL) Experience with vector databases or embedding-based search systems Background in a scientific or national security domain (e.g., environmental science, bioengineering, chemistry) is a plus Experience working in a research or government laboratory environment Responsibilities Design and implement knowledge management pipelines using large language models (LLMs), retrieval-augmented generation (RAG), and vector databases to enable intelligent information retrieval across large, multi-modal document corpora Develop and evaluate multi-agent AI architectures for automated reasoning, summarization, and decision support Build and maintain knowledge graphs and ontologies to represent complex domain relationships and support semantic search Collaborate with cross-functional research teams to integrate AI knowledge tools into existing scientific workflows and applications Author technical documentation, scientific journal articles, and internal reports communicating methods and findings to both technical and non-technical audiences Participate in code reviews and contribute to a shared, well-maintained research codebase Monitor and evaluate emerging developments in LLMs, agentic AI, and knowledge management frameworks, and assess their applicability to ongoing projects Qualifications Minimum Qualifications: Recent graduate (M.S. or Ph.D.) in Computer Science, Data Science, Information Science, or other scientific and engineering disciplines Strong proficiency in Python, including experience with AI/ML libra ries such as PyTorch, Hugging Face Transformers, or LangChain Foundational understanding of large language models, prompt engineering, and retrieval-augmented generation (RAG) Experience with or coursework in natural language processing (NLP) or knowledge representation Ability to clearly document and communicate technical research, including writing reports and presenting findings Self-directed with strong collaboration and interpersonal skills Must be able to obtain and maintain security clearance, for which U.S. Citizenship is legally required. Preferred Qualifications: Research experience or publications related to LLMs, knowledge graphs, information retrieval, or multi-agent systems Hands-on experience building end-to-end RAG pipelines or agentic AI workflows Familiarity with knowledge graph construction, ontology design, or semantic web technologies (RDF, SPARQL, OWL) Experience with vector databases or embedding-based search systems Background in a scientific or national security domain (e.g., environmental science, bioengineering, chemistry) is a plus Experience working in a research or government laboratory environment Organization SRNL’s Environmental & Legacy Management (ELM) Directorate closely collaborates with the Department of Energy (DOE) and site contractors to develop, mature, and apply science and technology needed to resolve environmental challenges and advance legacy management missions. As the lead laboratory for Environmental Management (DOE-EM) and Legacy Management (DOE-LM), SRNL applies our talent and expertise to develop and deploy innovative approaches and technologies to reduce risk, cost, and schedule of environmental cleanup and nuclear material processing. Additionally, ELM is using our competencies to develop new materials and processes for a range of clean energy applications. Company "We put science to work!" Savannah River National Laboratory (SRNL) is a multi-program laboratory applying state of the art science and practical, high-value, cost-effective solutions to complex technical problems to protect the nation. Located at the U.S. Department of Energy’s (DOE) Savannah River Site (SRS) in Aiken SC, the laboratory develops and deploys innovative technologies to address some of the nation’s environmental, energy, and national security challenges. Battelle Savannah River Alliance (BSRA) is constantly assessing trends to provide the best possible benefits to our workforce. We also negotiate cost effective premiums that will meet the needs of our evolving workforce. Some of the *Benefits offered to employees include: *Benefits vary based upon employment status Highly competitive Medical, Dental, and Vision options including HSA options with company provided seed Short- & Long-Term Disability (company paid) Life Insurance Non-Contributary 1X salary (company paid) AD&D Non-contributary 1x salary (company paid) Savings & Investment plan: Qualified Non-Elective Company Contribution of 5% each pay period with immediate vesting Company match 50 cents/dollar up to 8% (5 yrs. vesting in company match) Contributory Life Insurance up to 5x Salary with $1M Cap Contributory AD&D (employee, spouse and children) Paid Time Off Employee Assistance Plan SRNL offers a competitive relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. For more information about our benefits, working here, and living here, visit the “About” tab at www.srnl.doe.gov . BSRA is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected veteran status. BSRA is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. Please email us at [email protected] with any questions regarding the hiring process or to request an accommodation.
Salary Min1,000,000
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Source URLhttps://ewvl.fa.us8.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/2122
Apply URLhttps://ewvl.fa.us8.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/2122
First Seen At2026-05-31 18:06:59Z
Last Seen At2026-06-06 11:47:28Z
Last Checked At2026-06-06 11:47:28Z
Last Changed At2026-06-06 11:47:28Z
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Source Posted At2026-05-27 18:23:32Z
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    "ExternalQualificationsStr": "<div class=\"SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-text-stroke-width: 0px; -webkit-user-drag: none; background-color: rgb(255, 255, 255); color: rgb(0, 0, 0); font-family: &quot;Segoe UI&quot;, &quot;Segoe UI Web&quot;, Arial, Verdana, sans-serif; font-size: 12px; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; margin: 0px; orphans: 2; padding: 0px; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; user-select: text; white-space: normal; widows: 2; word-spacing: 0px;\"><div class=\"OutlineElement Ltr SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; direction: ltr; margin: 0px; overflow: visible; padding: 0px; position: relative; user-select: text;\"><p class=\"Paragraph SCXW57021422 BCX8\" role=\"heading\" aria-level=\"2\" paraid=\"2076473000\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{63}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: rgb(46, 116, 181); font-kerning: none; font-style: normal; margin: 13.3333px 0px 6.66667px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\">&nbsp;</p><p style=\"line-height: normal;\"><span style=\"font-family: &quot;Times New Roman&quot;, serif;\"><span style=\"font-size: 14pt;\"><strong>Minimum Qualifications:&nbsp;</strong></span></span></p><ul style=\"list-style-type: disc;\"><li style=\"line-height: normal;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Recent graduate (M.S. or Ph.D.) in Computer Science, Data Science, Information Science, or other scientific and engineering disciplines</span></span></li><li style=\"line-height: normal; margin-bottom: 0in; vertical-align: baseline;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Strong proficiency in&nbsp;</span></span><span style=\"font-family: &quot;Times New Roman&quot;, serif;\">Python, including experience with AI/ML libra</span><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">ries such as PyTorch, Hugging Face Transformers, or LangChain&nbsp;</span></span></li><li style=\"line-height: normal; margin-bottom: 0in; vertical-align: baseline;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Foundational understanding of large language models, prompt engineering, and retrieval-augmented generation (RAG)&nbsp;</span></span></li><li style=\"line-height: normal; margin-bottom: 0in; vertical-align: baseline;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Experience with or coursework in natural language processing (NLP) or knowledge representation&nbsp;</span></span></li><li style=\"line-height: normal; margin-bottom: 0in; vertical-align: baseline;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Ability to clearly document and communicate technical research, including writing reports and presenting findings&nbsp;</span></span></li><li style=\"line-height: normal; margin-bottom: 0in; vertical-align: baseline;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Self-directed with strong collaboration and interpersonal skills&nbsp;</span></span></li><li style=\"line-height: normal; margin-bottom: 0in; vertical-align: baseline;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Must be able to obtain and maintain security clearance, for which U.S. Citizenship is legally required.</span></span></li></ul><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"645740483\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{75}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\">&nbsp;</p><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"645740483\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{75}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\"><strong>Preferred Qualifications:&nbsp;</strong></span></span></p></div><div class=\"OutlineElement Ltr SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; direction: ltr; margin: 0px; overflow: visible; padding: 0px; position: relative; user-select: text;\"><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"751896649\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{77}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"1947596892\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{81}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Research experience or publications related to LLMs, knowledge graphs, information retrieval, or multi-agent systems</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"166060391\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{83}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Hands-on experience building end-to-end RAG pipelines or agentic AI workflows</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div></div><div class=\"SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-text-stroke-width: 0px; -webkit-user-drag: none; background-color: rgb(255, 255, 255); color: rgb(0, 0, 0); font-family: &quot;Segoe UI&quot;, &quot;Segoe UI Web&quot;, Arial, Verdana, sans-serif; font-size: 12px; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; margin: 0px; orphans: 2; padding: 0px; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; user-select: text; white-space: normal; widows: 2; word-spacing: 0px;\"><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"1392830767\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{85}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Familiarity with knowledge graph construction, ontology design, or semantic web technologies (RDF, SPARQL, OWL)</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"2121438675\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{88}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Experience with vector databases or embedding-based search systems</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"216707871\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{90}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Background in a scientific or national security domain (e.g., environmental science, bioengineering, chemistry) is a plus</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"585522251\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{92}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Experience working in a research or government laboratory environment</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div></div>",
    "InternalQualificationsStr": "<div class=\"SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-text-stroke-width: 0px; -webkit-user-drag: none; background-color: rgb(255, 255, 255); color: rgb(0, 0, 0); font-family: &quot;Segoe UI&quot;, &quot;Segoe UI Web&quot;, Arial, Verdana, sans-serif; font-size: 12px; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; margin: 0px; orphans: 2; padding: 0px; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; user-select: text; white-space: normal; widows: 2; word-spacing: 0px;\"><div class=\"OutlineElement Ltr SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; direction: ltr; margin: 0px; overflow: visible; padding: 0px; position: relative; user-select: text;\"><p class=\"Paragraph SCXW57021422 BCX8\" role=\"heading\" aria-level=\"2\" paraid=\"2076473000\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{63}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: rgb(46, 116, 181); font-kerning: none; font-style: normal; margin: 13.3333px 0px 6.66667px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\">&nbsp;</p><p style=\"line-height: normal;\"><span style=\"font-family: &quot;Times New Roman&quot;, serif;\"><span style=\"font-size: 14pt;\"><strong>Minimum Qualifications:&nbsp;</strong></span></span></p><ul style=\"list-style-type: disc;\"><li style=\"line-height: normal;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Recent graduate (M.S. or Ph.D.) in Computer Science, Data Science, Information Science, or other scientific and engineering disciplines</span></span></li><li style=\"line-height: normal; margin-bottom: 0in; vertical-align: baseline;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Strong proficiency in&nbsp;</span></span><span style=\"font-family: &quot;Times New Roman&quot;, serif;\">Python, including experience with AI/ML libra</span><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">ries such as PyTorch, Hugging Face Transformers, or LangChain&nbsp;</span></span></li><li style=\"line-height: normal; margin-bottom: 0in; vertical-align: baseline;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Foundational understanding of large language models, prompt engineering, and retrieval-augmented generation (RAG)&nbsp;</span></span></li><li style=\"line-height: normal; margin-bottom: 0in; vertical-align: baseline;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Experience with or coursework in natural language processing (NLP) or knowledge representation&nbsp;</span></span></li><li style=\"line-height: normal; margin-bottom: 0in; vertical-align: baseline;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Ability to clearly document and communicate technical research, including writing reports and presenting findings&nbsp;</span></span></li><li style=\"line-height: normal; margin-bottom: 0in; vertical-align: baseline;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Self-directed with strong collaboration and interpersonal skills&nbsp;</span></span></li><li style=\"line-height: normal; margin-bottom: 0in; vertical-align: baseline;\"><span style=\"font-family: Arial, sans-serif;\"><span style=\"font-size: 11pt;\">Must be able to obtain and maintain security clearance, for which U.S. Citizenship is legally required.</span></span></li></ul><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"645740483\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{75}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\">&nbsp;</p><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"645740483\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{75}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\"><strong>Preferred Qualifications:&nbsp;</strong></span></span></p></div><div class=\"OutlineElement Ltr SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; direction: ltr; margin: 0px; overflow: visible; padding: 0px; position: relative; user-select: text;\"><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"751896649\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{77}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"1947596892\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{81}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Research experience or publications related to LLMs, knowledge graphs, information retrieval, or multi-agent systems</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"166060391\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{83}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Hands-on experience building end-to-end RAG pipelines or agentic AI workflows</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div></div><div class=\"SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-text-stroke-width: 0px; -webkit-user-drag: none; background-color: rgb(255, 255, 255); color: rgb(0, 0, 0); font-family: &quot;Segoe UI&quot;, &quot;Segoe UI Web&quot;, Arial, Verdana, sans-serif; font-size: 12px; font-style: normal; font-variant-caps: normal; font-variant-ligatures: normal; font-weight: 400; letter-spacing: normal; margin: 0px; orphans: 2; padding: 0px; text-align: start; text-decoration-color: initial; text-decoration-style: initial; text-decoration-thickness: initial; text-indent: 0px; text-transform: none; user-select: text; white-space: normal; widows: 2; word-spacing: 0px;\"><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"1392830767\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{85}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Familiarity with knowledge graph construction, ontology design, or semantic web technologies (RDF, SPARQL, OWL)</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"2121438675\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{88}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Experience with vector databases or embedding-based search systems</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"216707871\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{90}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Background in a scientific or national security domain (e.g., environmental science, bioengineering, chemistry) is a plus</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"585522251\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{92}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Experience working in a research or government laboratory environment</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div></div>",
    "OrganizationDescriptionStr": "SRNL’s Environmental &amp; Legacy Management (ELM) Directorate closely collaborates with the Department of Energy (DOE) and site contractors to develop, mature, and apply science and technology needed to resolve environmental challenges and advance legacy management missions. As the lead laboratory for Environmental Management (DOE-EM) and Legacy Management (DOE-LM), SRNL applies our talent and expertise to develop and deploy innovative approaches and technologies to reduce risk, cost, and schedule of environmental cleanup and nuclear material processing.&nbsp; Additionally, ELM is using our competencies to develop new materials and processes for a range of clean energy applications.",
    "primaryLocationCoordinates": [
      {
        "Latitude": "33.56164",
        "Longitude": "-81.72214",
        "CountryCode": "US",
        "GeographyId": 300000004516803,
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    "ExternalResponsibilitiesStr": "<div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"763592902\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{16}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Design and implement knowledge management pipelines using large language models (LLMs), retrieval-augmented generation (RAG), and vector databases to enable intelligent information retrieval across large, multi-modal document corpora</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"686810759\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{18}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Develop and evaluate multi-agent AI architectures for automated reasoning, summarization, and decision support</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"376147086\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{20}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Build and maintain knowledge graphs and ontologies to represent complex domain relationships and support semantic search</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"922480720\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{22}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Collaborate with cross-functional research teams to integrate AI knowledge tools into existing scientific workflows and applications</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"2050950886\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{24}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Author technical documentation, scientific journal articles, and internal reports communicating methods and findings to both technical and non-technical audiences</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"1593351575\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{26}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Participate in code reviews and contribute to a shared, well-maintained research codebase</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"46302054\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{28}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Monitor and evaluate emerging developments in LLMs, agentic AI, and knowledge management frameworks, and assess their applicability to ongoing projects</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li><li class=\"OutlineElement Ltr SCXW57021422 BCX8\" aria-setsize=\"-1\" data-leveltext=\"•\" data-font=\"\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;•&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"7\" data-aria-level=\"1\" role=\"listitem\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; direction: ltr; display: block; font-family: Arial, Arial_MSFontService, sans-serif; font-size: 11pt; margin-bottom: 0px; margin-right: 0px; margin-top: 0px; overflow: visible; padding: 0px; position: relative; user-select: text; vertical-align: baseline;\"><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"46302054\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{28}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\">&nbsp;</p></li></ul></div><div class=\"OutlineElement Ltr SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; clear: both; cursor: text; direction: ltr; margin: 0px; overflow: visible; padding: 0px; position: relative; user-select: text;\"><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"2067240410\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{30}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></div>",
    "InternalResponsibilitiesStr": "<div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"763592902\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{16}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Design and implement knowledge management pipelines using large language models (LLMs), retrieval-augmented generation (RAG), and vector databases to enable intelligent information retrieval across large, multi-modal document corpora</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"686810759\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{18}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Develop and evaluate multi-agent AI architectures for automated reasoning, summarization, and decision support</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW57021422 BCX8\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; margin: 0px; padding: 0px; position: relative; user-select: text;\"><ul><li><p class=\"Paragraph SCXW57021422 BCX8\" paraid=\"376147086\" paraeid=\"{1687d0b9-cff0-431f-9569-072b0aba7473}{20}\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; background-color: transparent; color: windowtext; font-kerning: none; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Arial, Arial_EmbeddedFont, Arial_MSFontService, sans-serif;\"><span class=\"TextRun SCXW57021422 BCX8 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-tap-highlight-color: transparent; -webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17.2667px; margin: 0px; padding: 0px; user-select: text;\">Build and maintain knowledge graphs and ontologies to represent complex domain relationships and support semantic search</span><span class=\"EOP SCXW57021422 BCX8\" data-ccp-props=\"{}\" style=\"-webkit-tap-highlight-color: transparent; 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GET https://api.bluedoor.sh/job-postings/v1/jobs/4182f0e8edf5b4773e1bf8d1f132144f2913f37e?include=descriptionJSON
GET https://api.bluedoor.sh/job-postings/v1/orgs/27373ce2-efc8-4ffa-b547-2b4c63bdf5c2JSON
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