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to represent and interpret biological imaging data, enabling new scientific discoveries. Responsibilities include designing interpretable end-to-end machine learning frameworks to explain biomolecular condensate
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, learning, well-being, social experiences, and decision-making. HARP is developing a longitudinal multimodal research resource to study human-AI interaction and its impacts using student-informed, privacy
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Architecture: Architect, build, and evaluate multi-agent systems powered by LLMs and machine learning, incorporating Orchestrator and Memory agents, vector databases, and knowledge graphs to enable complex goal
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and machine learning with density functional theory, or other similarly relevant computational methods, to advance understanding of materials design predictions for 2D and 3D systems with electronic and
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brain MRI analysis, statistical analyses, as well as data acquisition and machine learning. Experience with stroke and federated learning is a plus. Job ID REQ20177725Posted Date 08/05/2026 Current
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; data analysis; modeling; statistics and machine learning; scientific simulation; or theoretical astrophysics. COMPENSATION AND BENEFITS The full-time annual compensation for this position is $95,000. In
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engineers. Apply machine learning techniques to develop VR/MR workforce-training applications for assembly and manufacturing tasks informed by models of expert engineering behavior. Collaborate with
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at the intersection of AI and any humanities or social science discipline. Fellows will have the option to teach one undergraduate course each year. The first year of appointment will run 1 August 2027–31 July 2028
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part of an AI-assisted mathematical research workflow. Write, modify, and debug computer programs and scripts. Use Python and, when necessary, learn other programming languages or computational tools
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engineers. Apply machine learning techniques to develop VR/MR workforce-training applications for assembly and manufacturing tasks informed by models of expert engineering behavior. Collaborate with