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care clinic, and collaborative spaces to strengthen its partnership with the University of Oxford. It will also host the Ellison Scholars, driving innovation for societal benefit. The Generative Biology
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Hutch is the only National Cancer Institute-designated cancer center in Washington. With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19
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to improve patient care. These efforts are enabled by our department's world-leading collection of brain tumour samples which are complemented by DNA methylation, DNA and RNA sequencing as well as clinical
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Are you interested in neuromorphic spintronic and can you contribute to the development of the project? Then the Department of Electrical and Computer Engineering invites you to apply for a one year
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increasing independence over time. Collaborate on project and analysis design guided by their PI. Develop new computational methods. Adhere to field and lab standards for data analysis. Identify, process
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the Human Pancreas Analysis Program (HPAP) and related consortia, providing access to deeply phenotyped T1D samples, islet organoids, and rich multi-omic datasets. Key Responsibilities Design and
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(e.g. R, Python) and an ability to work with large datasets Strong record of peer-reviewed publications Ability to independently design and execute experiments and interpret data Ability to work in a
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St. Jude is seeking outstanding candidates for postdoctoral fellowship positions in the Childhood Hematological Malignancies Training Program. This prestigious, NIH-sponsored T32 training program
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Postdoctoral Research Associate- Training in the Design & Development of Infectious Disease Therapeu
St. Jude is seeking outstanding candidates for postdoctoral fellowship positions in infectious disease therapeutics. This NIH sponsored training program has been designed to leverage the outstanding
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will