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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
be predicted using machine learning based on drug-specific information, patient demographics, and clinical trial data. 2. Modeling for Regulatory Science – Leveraging drug development and regulatory
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 5 hours ago
, and safety profiles, and how these relationships can be predicted using machine learning based on drug-specific information, patient demographics, and clinical trial data. 2. Modeling for Regulatory
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The University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 5 days ago
(""postdoc"") is a professional apprenticeship designed to provide recent Ph.D. recipients with an opportunity to develop further the research skills acquired in their doctoral programs or to learn new
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 8 hours ago
.) Departmental Preferred Experience, Skills, Training/Education: Ph.D. in design-related discipline, specializing in deep learning and biometrics. A strong background with evidence of experimental and AI/machine
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on machine learning or classical force fields. 3. Familiarity with open-source coding practices (GitHub/GitLab). More Information Location: Kent Ridge Campus Organization: College of Design and Engineering
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Bioinformatics, as well as the Departments of Biostatistics & Biomedical Engineering, University of Michigan is seeking a postdoctoral fellow for bioinformatics problems involving quantum machine learning and
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antigens, T cell receptor (TCR) and antigen interactions and their crucial role in anti-cancer immune responses. You'll leverage your strong background in computational biology, machine learning, and
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science discipline of interest to the Computing Sciences Area and Berkeley Lab. Alvarez Fellows apply advances in computer science, mathematics, computational science, data science, machine learning or AI
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nanofabrication is required. The postdoc is also expected to collaborate with other researchers to apply nanoelectronics and flexible electronics in biological and medical research. Basic Qualifications: Ph.D. in a
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, machine learning or AI to computational modeling, simulations, and advanced data analytics for scientific discovery in materials science, biology, astronomy, environmental science, energy, particle physics