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in projects related to simulation/mathematical/decision analytical modeling and cost-effectiveness analysis for harm reduction and other interventions aimed at preventing drug overdoses (primary focus
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Location ESOC, Darmstadt, Germany Our team and mission You will be part of the Mission Analysis Section in the Flight Dynamics Division at the European Space Operations Centre (ESOC). This Division
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The Kleinstein Lab (Program in Computational Biology and Biomedical Informatics) is seeking a highly motivated researcher in computational immunology to work in close collaboration with the Yildirim
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for Environmental Genomics (http://ieg.ou.edu/ ), led by Dr. Jizhong Zhou, has state-of-the-art facilities for the study of microbial functional genomics, microbial ecology, metagenomics, mathematical modeling, and
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with all institutional training and code of conduct. Ability to work independently based on experience. Knowledge of molecular dynamics simulation and mathematical modeling. Qualifications REQUIRED
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 22 hours ago
Research Associate Vacancy ID PDS004395 Full-time/Part-time Full-Time Temporary Hours per week 40 FTE 1 Work Location Chapel Hill, NC Position Location North Carolina, US Hiring Range Proposed Start Date 07
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for scientific and security applications; (ii) ML model optimization for inference speed and deployment for real-time analysis; and (iii) AI model training for analog in-memory computing. The position provides
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, foundation models, vision-language models, and computer vision for various problems relating to scientific discovery. Work in interdisciplinary collaborations with subject matter experts on various aspects
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-4-fold by both TGFb1, and/or HFD feeding) suggesting that Pcpe2 may play a role in TGFb-like signaling pathways in VAT PCs. We are looking for a creative post doctoral fellow who will assist in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
. The ideal candidate has research background and interests in one or more of the following areas: optimal transport (mathematical theory, computational analysis, machine learning applications), approximation