45 computer-science-intern "https:" "https:" "https:" "https:" "UCL" Fellowship positions at Nature Careers in United States
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Dana-Farber Cancer Institute, the Broad Institute, and more Mentor and guide junior staff and students Qualifications Ph.D. in bioinformatics, computational biology, statistics, data science, machine
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and expanding team. You’ll play a key role in our success through your code, publications, and strategic promotion of our work. * PhD in Computer Science, Biomedical Informatics, Machine Learning
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nervous system (CNS) tumors. We are seeking an exceptional candidate to join our Molecular and Cell Biology (MCB) Program. This position focuses on investigating DNA repair pathways in brain tumors, with
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of Population Sciences, seeks a highly motivated postdoctoral fellow in the McGraw/Patterson Center for Population Sciences. The Center is committed to population-based research aimed at detecting cancer early
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Area of research: Other Job description: Reference Number 10891 The Research Institute for Sustainability (RIFS) at the GFZ Helmholtz Centre for Geosciences is an international, inter-, and
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healthcare data. * A team player who thrives as a member of a highly functional cross-disciplinary team Preferred Elements * B.S, M.S., and/or PhD in Computer Science, Biomedical Informatics, Machine Learning
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computational modeling, in vivo biological assays, and radiation physics and engineering approaches to define the mechanisms and optimal radiation dosimetric parameters by which FLASH-RT mitigates radiation
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of genomic stability and DNA repair mechanisms in human cancers. The candidate will work in a cutting-edge research environment with access to advanced molecular biology tools and technologies. Located in
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-performance computing clusters (>105,000 processors). This unique interdisciplinary environment emphasizes the integration of AI in life sciences, offering an outstanding platform for recent Ph.D. graduates
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cancer patients. The lab employs cutting-edge technologies (immunopeptidomics, T cell engineering, single-cell transcriptomics, spatial transcriptomics, CRISPR technologies) paired with in vivo animal