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    "ShortDescriptionStr": "The Research Engineer will develop and integrate intelligent additive manufacturing systems that combine in-situ sensing, data acquisition, computer vision, and digital twin technologies. This role focuses on building experimental and computational tools for real-time process monitoring, data fusion, and predictive modeling of material behavior.",
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    "ExternalDescriptionStr": "<p><span>The Research Engineer will develop and integrate intelligent additive manufacturing systems that combine in-situ sensing, data acquisition, computer vision, and digital twin technologies. This role focuses on building experimental and computational tools for real-time process monitoring, data fusion, and predictive modeling of material behavior.</span></p><p><span>The position is hands-on and applied, involving system integration, algorithm development, and experimental validation in collaboration with multidisciplinary engineering teams.</span></p><p style=\"line-height: normal;\"><span>Electrical Engineering has been primarily responsible for the information technology revolution that society is experiencing. The development of large-scale integrated circuits has led to the development of computers and networks of ever-increasing capabilities. Computers greatly influence the methods used by engineers for designing and problem solving.</span></p><p style=\"line-height: normal;\"><span><strong>Duties and Responsibilities</strong></span></p><ul><li><p style=\"line-height: normal;\"><span>Design, develop, and optimize additive manufacturing systems (laser powder bed fusion, directed energy deposition, or extrusion-based platforms).</span></p></li><li><p style=\"line-height: normal;\"><span>Develop and integrate in-situ sensing and monitoring systems using multi-modal sensors (thermal, optical, acoustic, and process signals).</span></p></li><li><p style=\"line-height: normal;\"><span>Build and deploy data acquisition and real-time data pipelines for manufacturing process monitoring.</span></p></li><li><p style=\"line-height: normal;\"><span>Implement data fusion and signal processing algorithms to integrate heterogeneous sensor data streams.</span></p></li><li><p style=\"line-height: normal;\"><span>Develop and maintain digital twin frameworks for simulation, prediction, and real-time process feedback.</span></p></li><li><p style=\"line-height: normal;\"><span>Apply computer vision and image processing techniques (e.g., melt pool monitoring, layer inspection, defect detection).</span></p></li><li><p style=\"line-height: normal;\"><span>Develop models linking process parameters, sensor data, and material properties (strength, fatigue, microstructure).</span></p></li><li><p style=\"line-height: normal;\"><span>Support mechanical testing and materials characterization to validate models and system performance.</span></p></li><li><p style=\"line-height: normal;\"><span>Collaborate closely with teams in mechanical engineering, materials science, data science, and systems engineering.</span></p></li><li><p style=\"line-height: normal;\"><span>Contribute to technical documentation, system reports, and internal/external presentations for stakeholders and collaborators.</span></p></li></ul><p style=\"line-height: normal;\"><span>Supervisory Relationships: This position has no supervisory responsibilities; this position will report directly to Professor Shekhar Bhansali.</span></p><p style=\"line-height: normal;\"><span><strong>Qualifications</strong></span></p><ul style=\"list-style-type: disc;\"><li><p style=\"line-height: normal;\"><span>A Ph.D. or a Master’s Degree in Electrical Engineering, Mechanical Engineering, Materials Science, Manufacturing Engineering, Computer Engineering, or related field (Ph.D. preferred for advanced responsibilities).</span></p></li><li><p style=\"line-height: normal;\"><span>Strong experience with additive manufacturing systems and process fundamentals.</span></p></li><li><p style=\"line-height: normal;\"><span>Hands-on experience with sensing systems, instrumentation, and data acquisition hardware/software.</span></p></li><li><p style=\"line-height: normal;\"><span>Proficiency in Python and/or MATLAB for data analysis and algorithm development.</span></p></li><li><p style=\"line-height: normal;\"><span>Experience with machine learning, signal processing, or data fusion techniques applied to real-world systems.</span></p></li><li><p style=\"line-height: normal;\"><span>Strong background in image processing and computer vision (e.g., OpenCV or equivalent toolkits).</span></p></li><li><p style=\"line-height: normal;\"><span>Familiarity with modeling, simulation, or digital twin development frameworks.</span></p></li><li><p style=\"line-height: normal;\"><span>Understanding of materials behavior and structure–property relationships.</span></p></li><li><p style=\"line-height: normal;\"><span>Strong problem-solving skills with ability to work in experimental and applied engineering environments.</span></p></li><li><p style=\"line-height: normal;\"><span>Excellent communication skills and ability to work effectively in cross-disciplinary teams.</span></p></li><li><p style=\"line-height: normal;\"><span>Experience with real-time control systems or closed-loop feedback systems.</span></p></li><li><p style=\"line-height: normal;\"><span>Knowledge of metallurgy and microstructure evolution in additively manufactured materials.</span></p></li><li><p style=\"line-height: normal;\"><span>Experience with high-performance computing (HPC) or cloud-based simulation environments.</span></p></li><li><p style=\"line-height: normal;\"><span>Experience transitioning research prototypes into deployable engineering systems or industrial applications.</span></p></li><li><p style=\"line-height: normal;\"><span>Familiarity with software engineering best practices (version control, modular design, reproducibility).</span></p></li></ul>",
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