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and industrial project partners. You will be responsible for: Developing and adapting machine-learning approaches for structure-based and generative molecular design. Integrating physicochemical
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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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Program Description Overview The IAS School of Mathematics welcomes applications from mathematicians and theoretical computer scientists at all career levels, and mid-career scientists (5-15 years
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Cognitive Science, Medical Informatics, or a comparable quantitative discipline Proven hands-on experience working with LLMs, foundation models, multimodal AI systems, or related machine-learning technologies
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to work collaboratively with others and contribute to a team environment. Technical Proficiency: Skilled in using office software, technology, and relevant computer applications. Communication: Strong and
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, pharmacology, genomics and multi-omics, as well as growing methods in advanced analytics of health data e.g. machine learning to improve human health with a focus on therapeutics. These posts will work alongside
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is represented exclusively by Postdocs United/United Automobile, Aerospace and Agricultural Implement Workers of America (UAW) under the Collective Bargaining Agreement (CBA). Information regarding
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is represented exclusively by Postdocs United/United Automobile, Aerospace and Agricultural Implement Workers of America (UAW) under the Collective Bargaining Agreement (CBA). Information regarding
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, marital or domestic partnership or civil union status, sex, pregnancy, gender identity or expression, disability status, liability for military service, protected veteran status, affectional or sexual
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of qualification for employment has been made. Union Representation: This position is represented exclusively by Postdocs United/United Automobile, Aerospace and Agricultural Implement Workers of America (UAW) under