Spatial Analyst Researcher in Residence

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    "jobTitle": "Spatial Analyst Researcher in Residence",
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    "description": "<p>&nbsp;</p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">The New Mexico Forest and Watershed Restoration Institute (NMFWRI) is seeking a full-time (100% FTE) postdoctoral scholar with expertise in fire modeling and remotely sensed data to support innovative research. This project will improve our understanding of the conditions under which fuel treatments effect wildfire behavior and to evaluate long term post fire impacts within the Hermit&rsquo;s Peak Calf Canyon Fire burn scar.</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">As NMFWRI is part of the Southwest Ecological Restoration Institutes (SWERI), The postdoctoral scholar will join a collaborative team of researchers, on the grant funded ReSHAPE project <a href=\"https://reshapewildfire.org/\" rel=\"noreferrer noopener\" style=\"color:#467886;text-decoration:underline;\" target=\"_blank\">https://reshapewildfire.org/</a>.&nbsp; The researcher will incorporate fuel treatment databases currently being developed as part of the national Treatment and Wildfire Interagency Geodatabase (TWIG). This researcher will leverage existing spatial data on landscapes, fire behavior, and fuel treatments to evaluate real-world wildfire-treatment encounters across diverse U.S. landscapes. The researcher will work closely with the staff of the three SWERIs to coordinate research using TWIG to ensure data quality and specificity is additive to potential uses, end users and analyses.</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">The incumbent will be responsible for processing and analyzing large remote sensing datasets (e.g., Landsat, Sentinel-2, MODIS) and spatial datasets (e.g., TWIG, FACTs, FTEM, field data) both locally with R/Python and via Google Earth Engine for treatment outcome research. Work will include analysis of spatial and related data (vector, raster, imagery) sufficient to support multi-scale and/or multi-resource assessments and monitoring. Knowledge of data and data management sufficient to create, transform and integrate data in a variety of resolutions and formats is necessary. Analysis will include running machine learning algorithms (e.g., Random Forest, CART) and regression models to derive ecological insights from big data sets. The project entails developing reproducible and scalable methodologies, using common software and programming languages, that can be used by land managers for decision making support.</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\">&nbsp;</p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">We take care of our own! </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Once hired, our Spatial Analyst Post Doc will be mentored by experienced GIS professionals and have a chance to teach us a thing or two as well! They will have many opportunities for professional development such as attending conferences and presenting their research. They will work with a passionate team engaged in and excited about education, ecological monitoring, and collaborative conservation. </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">As a New Mexico Highlands University employee, benefits include superb health, paid leave, and retirement benefits, an extended winter holiday break, and tuition waivers at New Mexico Highlands University.</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">&nbsp;</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Where you will work.</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">NMFWRI&rsquo;s Spatial Analyst Post Doc will have the option for hybrid /remote work but must be willing to travel to New Mexico on a quarterly basis and attend regular virtual (zoom) meetings. In-state and out-of-state travel will be required, including attending conferences and regional meetings.&nbsp; Approved travel costs will be reimbursed. </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\">&nbsp;</p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">DUTIES AND RESPONSIBILITIES:&nbsp; </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">The incumbent will be responsible for processing and analyzing large remote sensing datasets (e.g., Landsat, Sentinel-2, MODIS) and spatial datasets (e.g., TWIG, FACTs, FTEM, field data) both locally with R/Python and via Google Earth Engine for treatment outcome research. </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Work will include analysis of spatial and related data (vector, raster, imagery) sufficient to support multi-scale and/or multi-resource planning, assessments, and monitoring. Knowledge of data and data management sufficient to create, transform and integrate data in a variety of resolutions and formats.</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Project management, leading analysis, modeling, and visualization efforts, and coordinating project communication.</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Use of project management software to track project tasks (e.g. GitHub) </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Prepare and submit manuscripts for publication in scholarly journals </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Work successfully in a team environment and collaborate effectively with other research partners. </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Prepare, deliver and contribute to the production, communication, and publication or dissemination of high-quality science-based products for use by scientist, managers and/or collaborative forestry groups</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">PHYSICAL DEMANDS:</span></span></span></p>\r\n\r\n<p style=\"margin-left:48px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Standing&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;Frequently</span></span></span></p>\r\n\r\n<p style=\"margin-left:48px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Sitting &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Frequently</span></span></span></p>\r\n\r\n<p style=\"margin-left:48px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Walking (cross country) &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Infrequently</span></span></span></p>\r\n\r\n<p style=\"margin-left:48px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Bending&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Infrequently</span></span></span></p>\r\n\r\n<p style=\"margin-left:48px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Squatting&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Infrequently</span></span></span></p>\r\n\r\n<p style=\"margin-left:48px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Kneeling&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Infrequently</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;margin-left:48px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Lifting (30lbs or less)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Infrequently</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\">&nbsp;</p>\r\n\r\n<p>&nbsp;</p>\r\n",
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This project will improve our understanding of the conditions under which fuel treatments effect wildfire behavior and to evaluate long term post fire impacts within the Hermit&rsquo;s Peak Calf Canyon Fire burn scar.\\r\\n\\r\\nAs NMFWRI is part of the Southwest Ecological Restoration Institutes (SWERI), The postdoctoral scholar will join a collaborative team of researchers, on the grant funded ReSHAPE project https://reshapewildfire.org/.&nbsp; The researcher will incorporate fuel treatment databases currently being developed as part of the national Treatment and Wildfire Interagency Geodatabase (TWIG). This researcher will leverage existing spatial data on landscapes, fire behavior, and fuel treatments to evaluate real-world wildfire-treatment encounters across diverse U.S. landscapes. 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The project entails developing reproducible and scalable methodologies, using common software and programming languages, that can be used by land managers for decision making support.\\r\\n\\r\\n&nbsp;\\r\\n\\r\\nWe take care of our own! \\r\\n\\r\\nOnce hired, our Spatial Analyst Post Doc will be mentored by experienced GIS professionals and have a chance to teach us a thing or two as well! They will have many opportunities for professional development such as attending conferences and presenting their research. They will work with a passionate team engaged in and excited about education, ecological monitoring, and collaborative conservation. \\r\\n\\r\\nAs a New Mexico Highlands University employee, benefits include superb health, paid leave, and retirement benefits, an extended winter holiday break, and tuition waivers at New Mexico Highlands University.\\r\\n\\r\\n&nbsp;\\r\\n\\r\\nWhere you will work.\\r\\n\\r\\nNMFWRI&rsquo;s Spatial Analyst Post Doc will have the option for hybrid /remote work but must be willing to travel to New Mexico on a quarterly basis and attend regular virtual (zoom) meetings. In-state and out-of-state travel will be required, including attending conferences and regional meetings.&nbsp; Approved travel costs will be reimbursed. \\r\\n\\r\\n&nbsp;\\r\\n\\r\\nDUTIES AND RESPONSIBILITIES:&nbsp; \\r\\n\\r\\nThe incumbent will be responsible for processing and analyzing large remote sensing datasets (e.g., Landsat, Sentinel-2, MODIS) and spatial datasets (e.g., TWIG, FACTs, FTEM, field data) both locally with R/Python and via Google Earth Engine for treatment outcome research. \\r\\n\\r\\nWork will include analysis of spatial and related data (vector, raster, imagery) sufficient to support multi-scale and/or multi-resource planning, assessments, and monitoring. Knowledge of data and data management sufficient to create, transform and integrate data in a variety of resolutions and formats.\\r\\n\\r\\nProject management, leading analysis, modeling, and visualization efforts, and coordinating project communication.\\r\\n\\r\\nUse of project management software to track project tasks (e.g. GitHub) \\r\\n\\r\\nPrepare and submit manuscripts for publication in scholarly journals \\r\\n\\r\\nWork successfully in a team environment and collaborate effectively with other research partners. \\r\\n\\r\\nPrepare, deliver and contribute to the production, communication, and publication or dissemination of high-quality science-based products for use by scientist, managers and/or collaborative forestry groups\\r\\n\\r\\nPHYSICAL DEMANDS:\\r\\n\\r\\nStanding&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;Frequently\\r\\n\\r\\nSitting &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Frequently\\r\\n\\r\\nWalking (cross country) &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Infrequently\\r\\n\\r\\nBending&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Infrequently\\r\\n\\r\\nSquatting&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Infrequently\\r\\n\\r\\nKneeling&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Infrequently\\r\\n\\r\\nLifting (30lbs or less)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Infrequently\\r\\n\\r\\n&nbsp;\\r\\n\\r\\n&nbsp;\\r\\nQualifications&nbsp;\\r\\n\\r\\nEDUCATION:&nbsp; \\r\\n\\r\\nPhD in forestry, ecology, natural resources, wildland fire science, or geography.\\r\\n\\r\\nEXPERIENCE: \\r\\n\\r\\nMore than 2 years programming experience using software such R, and R Studio for spatial data processing and analysis. \\r\\n\\r\\nMore than 1 years programming experience using Google Earth Engine for spatial data processing and analysis. \\r\\n\\r\\nExperience automating spatial analysis workflows with remote sensing, multiple data types (spreadsheets, databases, raster and vector spatial data), big data, or spatial analysis across multiple software platforms.\\r\\n\\r\\nEvidence of expertise in fire behavior and/or fire management in the western US\\r\\n\\r\\nEvidence of expertise or experience using geospatial data analytics and products. \\r\\n\\r\\nEvidence or experience in collaborating, motivating and encouraging staff to perform at a high level \\r\\n\\r\\nEvidence of professional oral communication to diverse audiences. \\r\\n\\r\\nDemonstrated research accomplishments and peer-reviewed publications. \\r\\n\\r\\nEvidence of personal or professional commitment to diversity as demonstrated by persistent effort, active planning, allocation of resources and/or accountability.\\r\\n\\r\\nExperience with fire behavior modeling programs (e.g., FlamMap, FSIM, etc). \\r\\n\\r\\nEvidence of supervision of others in collaborative project settings \\r\\n\\r\\nKnowledge of western US forest and fire ecology, wildfire management, and/or wildfire experience. \\r\\n\\r\\nExperience with cloud/ cluster computing to fit large models.\\r\\n\\r\\n&nbsp;\\r\\n\\r\\n&nbsp;\\r\\n\\r\\nPreferred Skills\\r\\n\\r\\n&nbsp;\\r\\n\\r\\n&nbsp;\\r\\n\\r\\nExpertise in GIS, remote sensing, and statistics and programming proficiency in R, Python, Google Earth Engine or similar languages. \\r\\n\\r\\nBackground in natural resource management applications and wildland fire sciences.\\r\\n\\r\\nExperience processing and analyzing large remote sensing datasets.\\r\\n\\r\\nExpertise in fire science, fire behavior models, and fuel mapping.\\r\\n\\r\\nWorking knowledge of forest or ecosystem dynamics and disturbance ecology \\r\\n\\r\\nProficient with running machine learning algorithms (e.g., Random Forest, CART) and regression models to derive ecological insights from big data sets.\\r\\n\\r\\nStrong interpersonal and communication skills.\\r\\n\\r\\n&nbsp;\\r\\n\",\"responsibilities\":\"&nbsp;\\r\\n\\r\\nThe New Mexico Forest and Watershed Restoration Institute (NMFWRI) is seeking a full-time (100% FTE) postdoctoral scholar with expertise in fire modeling and remotely sensed data to support innovative research. This project will improve our understanding of the conditions under which fuel treatments effect wildfire behavior and to evaluate long term post fire impacts within the Hermit&rsquo;s Peak Calf Canyon Fire burn scar.\\r\\n\\r\\nAs NMFWRI is part of the Southwest Ecological Restoration Institutes (SWERI), The postdoctoral scholar will join a collaborative team of researchers, on the grant funded ReSHAPE project https://reshapewildfire.org/.&nbsp; The researcher will incorporate fuel treatment databases currently being developed as part of the national Treatment and Wildfire Interagency Geodatabase (TWIG). This researcher will leverage existing spatial data on landscapes, fire behavior, and fuel treatments to evaluate real-world wildfire-treatment encounters across diverse U.S. landscapes. The researcher will work closely with the staff of the three SWERIs to coordinate research using TWIG to ensure data quality and specificity is additive to potential uses, end users and analyses.\\r\\n\\r\\nThe incumbent will be responsible for processing and analyzing large remote sensing datasets (e.g., Landsat, Sentinel-2, MODIS) and spatial datasets (e.g., TWIG, FACTs, FTEM, field data) both locally with R/Python and via Google Earth Engine for treatment outcome research. Work will include analysis of spatial and related data (vector, raster, imagery) sufficient to support multi-scale and/or multi-resource assessments and monitoring. Knowledge of data and data management sufficient to create, transform and integrate data in a variety of resolutions and formats is necessary. Analysis will include running machine learning algorithms (e.g., Random Forest, CART) and regression models to derive ecological insights from big data sets. The project entails developing reproducible and scalable methodologies, using common software and programming languages, that can be used by land managers for decision making support.\\r\\n\\r\\n&nbsp;\\r\\n\\r\\nWe take care of our own! \\r\\n\\r\\nOnce hired, our Spatial Analyst Post Doc will be mentored by experienced GIS professionals and have a chance to teach us a thing or two as well! They will have many opportunities for professional development such as attending conferences and presenting their research. They will work with a passionate team engaged in and excited about education, ecological monitoring, and collaborative conservation. \\r\\n\\r\\nAs a New Mexico Highlands University employee, benefits include superb health, paid leave, and retirement benefits, an extended winter holiday break, and tuition waivers at New Mexico Highlands University.\\r\\n\\r\\n&nbsp;\\r\\n\\r\\nWhere you will work.\\r\\n\\r\\nNMFWRI&rsquo;s Spatial Analyst Post Doc will have the option for hybrid /remote work but must be willing to travel to New Mexico on a quarterly basis and attend regular virtual (zoom) meetings. In-state and out-of-state travel will be required, including attending conferences and regional meetings.&nbsp; Approved travel costs will be reimbursed. \\r\\n\\r\\n&nbsp;\\r\\n\\r\\nDUTIES AND RESPONSIBILITIES:&nbsp; \\r\\n\\r\\nThe incumbent will be responsible for processing and analyzing large remote sensing datasets (e.g., Landsat, Sentinel-2, MODIS) and spatial datasets (e.g., TWIG, FACTs, FTEM, field data) both locally with R/Python and via Google Earth Engine for treatment outcome research. \\r\\n\\r\\nWork will include analysis of spatial and related data (vector, raster, imagery) sufficient to support multi-scale and/or multi-resource planning, assessments, and monitoring. 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style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">More than 1 years programming experience using Google Earth Engine for spatial data processing and analysis. </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Experience automating spatial analysis workflows with remote sensing, multiple data types (spreadsheets, databases, raster and vector spatial data), big data, or spatial analysis across multiple software platforms.</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Evidence of expertise in fire behavior and/or fire management in the western US</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Evidence of expertise or experience using geospatial data analytics and products. </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Evidence or experience in collaborating, motivating and encouraging staff to perform at a high level </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Evidence of professional oral communication to diverse audiences. </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Demonstrated research accomplishments and peer-reviewed publications. </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Evidence of personal or professional commitment to diversity as demonstrated by persistent effort, active planning, allocation of resources and/or accountability.</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Experience with fire behavior modeling programs (e.g., FlamMap, FSIM, etc). </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Evidence of supervision of others in collaborative project settings </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Knowledge of western US forest and fire ecology, wildfire management, and/or wildfire experience. </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Experience with cloud/ cluster computing to fit large models.</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\">&nbsp;</p>\r\n\r\n<p>&nbsp;</p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><b><u>Preferred Skills</u></b></span></span></span></p>\r\n\r\n<p>&nbsp;</p>\r\n\r\n<p style=\"margin-bottom:11px;margin-left:48px;\">&nbsp;</p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Expertise in GIS, remote sensing, and statistics and programming proficiency in R, Python, Google Earth Engine or similar 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disturbance ecology </span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Proficient with running machine learning algorithms (e.g., Random Forest, CART) and regression models to derive ecological insights from big data sets.</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\">Strong interpersonal and communication skills.</span></span></span></p>\r\n\r\n<p style=\"margin-bottom:11px;\">&nbsp;</p>\r\n",
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