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learning methods development and application. The postdoc associates will be exposed to rich multi-omics data, a variety of diseases, advanced statistical and machine learning methods and wide collaborations
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by Dr. Tim Pleskac (cognitive and decision modeling) and Dr. David Crandall (computer vision and AI). The postdoc will lead the development, integration, and testing of computational models of decision
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Familiarity with immune profiling and systems immunology in infectious diseases or critical illness, including sepsis Experience with machine learning approaches for biomedical datasets Planning and preparation
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Surgery Stanford Departments and Centers: Surgery, General Surgery Postdoc Appointment Term: 1 year Appointment Start Date: July 1, 2026 Group or Departmental Website: https://med.stanford.edu/gensurg
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
the nation for federal research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our
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for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
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on advanced machine learning and emulation approaches. Key responsibilities: The candidates will be expected to work on the following tasks: - Develop machine learning (ML) methodologies appropriate
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modeling approaches-including machine learning (ML), hydrologic and energy systems simulations, and scenario forecasting-to evaluate dynamic energy-water futures and resilience strategies for diverse Idaho
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for machine learning models to optimise membrane properties, structure, and fabrication. The fellow will play a key role in the experimental part of the project, including: Preparation and characterisation
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of the Research Project(s): The goal of our research is to develop vaccines and therapeutics targeting human pathogens. Duties and Responsibilities: 20% Structure-based and machine-learning immunogen design for