283 computational-physics "https:" "https:" "https:" "https:" "U.S" Postdoctoral positions at Nature Careers
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Postdoctoral Research Associate - Basic and Translational Research Training in Pediatric Classical H
-malignant blood diseases, such as sickle cell disease, bone marrow failure syndromes, and myeloproliferative disorders. This premier NHLBI-sponsored T32 training program leverages the exceptional research
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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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Postdoctoral Research Associate - Training in Pediatric Cancer Survivorship Outcomes and Interventio
; a top-ranked scientific environment; and superb benefits, mentoring, and professional development. Positions are available in diverse research areas, including epidemiology, genetics, computational
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degree in Electrical Engineering, Telecommunications Engineering, Computer Science, Applied Physics, or a closely related field Strong background in communication systems, signal processing, and applied
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, sequencing, automation, imaging, and bioprocessing. GBI will also have access to substantial compute resources that can be leveraged to further accelerate progress, including scientific compute, bioinformatics
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-year period and is funded by a Carlsberg Foundation Accomplish Grant to Prof. Nanna B. Karlsson. About the position This position is part of the research programme REGLA, investigating the physical
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sustainable process development. Opportunities to contribute to an ambitious research program (HyperCap) advancing novel carbon capture technologies toward pilot-scale demonstration. A supportive and
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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: (1) the chemical
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or computational approaches to study biological systems in close collaboration with experimental groups at the MPI-CBG and the TUD. Ideal candidates should have backgrounds in physics, computer science, mathematics
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, and train deep learning models on the resulting data to design new antibiotic compounds that evade both current and likely future resistance mechanisms. Your computational work will directly steer