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Field
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workers, staff, and faculty to teach and support these workshops. 3. Assist with the development and support of funded DH scholarship, both at USM and at partner institutions across the state, including
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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and
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healthcare access and outcomes for high-risk patients. The postdoctoral researcher will play a key role in translating machine learning algorithms into professional software with an intuitive user interface
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Postdoctoral Researcher position in AI and machine learning, with a focus on patient-specific reconstruction of coronary vessels and the simulation of stenting techniques using Finite Element Analysis (FEA) and
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analysis of atmospheric numerical model output (e.g., WRF, PALM, SAM) Experience with machine learning and artificial intelligence techniques Experience with predictive modeling Environmental, Health
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. Use of radiation transport codes, especially MCNP, Serpent, OpenMC, or an equivalent code. Experience with uncertainty quantification methods. Experience with computer programming (Python, C
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information, remote sensing data, and GIS software. Experience in deep learning and computer vision. Experience in developing software tools and products. Experience in writing scientific papers and successful
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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based on predictions from statistical and machine learning models Postdoctoral scholars are represented by UAW 4121 and are subject to the collective bargaining agreement, unless agreed exclusion criteria
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community and attend conferences yearly, preferably delivering a podium presentation or poster. Opportunities exist to learn about user-inspired research planning, intellectual property management, technology