73 machine-learning-"https:" "https:" "https:" positions at Nature Careers in United States
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team member in the CBSC focused on ligand discovery, joining a team of dedicated computational researchers with diverse expertise ranging from structural bioinformatics to machine learning and AI. Your
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questions relevant to the advancement of human health. Appointees are expected to teach at the undergraduate or graduate level. The University of Chicago is a vibrant center of scientific discovery and
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cohorts and data generation resources through highly collaborative clinical faculty. Ideal candidates will have expertise in computational modeling, machine learning, or algorithm development, with
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cohorts and data generation resources through highly collaborative clinical faculty. Ideal candidates will have expertise in computational modeling, machine learning, or algorithm development, with
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research. These new faculty positions represents part of a major research initiative by VT located at both our main medical center campus in Roanoke (https://hst.vt.edu/campus.html ) as well as our facility
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of immune cell function. These projects are focused on making safer and more effective cell therapies (e.g., CAR-T) and gene therapies for cancer and beyond. We are an interdisciplinary lab spanning
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training and research focus in statistics, data science, machine learning or artificial intelligence (as evidenced by thesis/dissertation topic and their publication record), and hold a PhD (or equivalent
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modelling, stem cell biology (animal-/humanderived tissues), micro-physiological systems (MPS), organ-on-chip, zoonotic diseases, drug/vaccine testing and validation for zoonotic diseases, machine learning in
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Job Description Project Description: Drug toxicity and resistance are the leading causes of therapeutic failures. The Chen Lab (https://www.stjude.org/research/labs/chen-lab-taosheng.html) studies
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The AITHYRA-CeMM Joint International PhD Call in Molecular Medicine and Artificial Intelligence (m/f
for both life scientists and computational scientists/machine learning experts will start in September 2026. We offer: a highly interactive introductory program in a supportive peer-group environment