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Field
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and machine learning projects involving heterogeneous data. S/he is expected to collaborate and exchange with the previous experts involved in the project and to produce efficient work to achieve
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models of therapeutic response using machine learning combined with Fourier-Transform Infrared Spectroscopy (FTIR) applied to blood, saliva, and tumor tissue samples. Requirements: PhD completed by
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individual to join this exciting collaborative research program that builds upon existing strengths in ADRD biology and genetics (JAX) and bioinformatics methods and machine learning approaches (Roux
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-Coding Genome Edits: Develop innovative machine learning approaches for designing precise non-coding genome edits, focusing on how non-coding alterations influence gene regulation and cellular function
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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | about 1 month ago
program at The Hospital for Sick Children, University of Toronto, and the Vector Institute. Our research group focuses on developing machine learning-based pipelines that leverage generative models and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days 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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statistical physics. Specific Requirements Preference will be given to candidates with experience in research related to machine learning, graph theory, statistical physics, and modeling of stochastic systems
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months 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 | about 2 months 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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innovative development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. More specifically, at NRM this research will be