46 programming-"Multiple"-"U"-"Humboldt-Stiftung-Foundation" "Prof" Postdoctoral positions at The Ohio State University
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cancer program in the United States that features a National Cancer Institute (NCI)-designated comprehensive cancer center aligned with a nationally ranked academic medical center and a freestanding cancer
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/ML methods. Prior experience with analyzing real-world databases, especially claims and EHR databases. Prior experience with cloud computing. Strong programming skills using at least one of the
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of RNases related to human health and disease. The Post Doctoral Scholar will embark on a program of independent research with the primary goal to determine how RNases regulate gene expression in the cell
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zone settings. The Post Doctoral Scholar will embark on a program of independent research with the primary goal to determine current-day slope stability in the southern Cascadia offshore margin based
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designing and executing observing programs for current and future X-ray observatories. Successful candidates will be expected to: 1. Lead a vigorous research program in the observational study of black hole
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(or a related field), is proficient in both mechanistic modeling and ML frameworks (e.g., TensorFlow, PyTorch), and has strong programming skills (Python/MATLAB/C++). Join us to tackle sustainability
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| Comprehensive Cancer Center Institution: The Ohio State University Comprehensive Cancer Center (OSUCCC) Program: Cancer Prevention and Control Training Program (CPCTP) Location: Columbus, Ohio Position: NRSA
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/ Statistical Genetics or closely related program. Required Qualifications Ph.D. degree in bioinformatics, statistical genetics, biostatistics, or a closely aligned quantitative area. Candidate is expected
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in the scientific field and accounts for previously unexplained phenomena for new and/or continuing research projects; participate in determining priorities and planning research programs; carry out
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personalized biomechanical modeling research and development efforts. In this role, they will help develop and incorporate new model features into existing laboratory models and programs. They will support the