160 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" positions at Nature Careers in United States
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Description: The Medical University of Vienna is recruiting for up to 24 fully funded PhD positions across 18 interdisciplinary PhD programs. Research spans translational basic and clinical science
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about the PI’s research, please visit http://yanglab.me . The University of Chicago is a global leader in biomedical research and offers unique opportunities for multidisciplinary collaboration
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or datasets for metabolite discovery from small molecule mass spectrometry (e.g., https://www.nature.com/articles/s41586-025-09969-x, https://www.nature.com/articles/s42256-021-00407-x, https://www.nature.com
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T cell biology or cancer immunology, and programming skills (R, Python) for data analysis. Please also read recent manuscripts published in the last two years 2024 Nature: (https://www.nature.com
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Vision 401(k) with company match and contribution Hybrid office working policy, Summer Hours, and paid time off Flexible Spending and Commuter programs Multiple Life insurance options Disability coverage
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publication record in immunology/epigenetics. Information on our postdoctoral training program, benefits, and a virtual tour can be found at http://www.utsouthwestern.edu/postdocs . Please also read recent
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sciences compensation plan which provides for eligibility for additional compensation. Apply online at https://aprecruit.ucsf.edu/JPF05877 . The University of California is an Equal Opportunity Employer
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at: (http://www.bumc.bu.edu/anatneuro/ ). The successful applicant will join a strong and growing Boston University interdisciplinary neuroscience research community where departmental research programs have
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, progression, and therapeutic response. This research is fundamental to advancing our knowledge of cancer and improving patient outcomes. See further information at the lab webpage: https://odin.mdacc.tmc.edu
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fellow to join our translational research program in macrophage biology/immunology. Our team takes a systems approach—integrating multi-omics, network science, machine learning, and comprehensive in vitro