280 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" "St" Postdoctoral positions at Nature Careers
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: https://obgyn.uchicago.edu/research/griffith-laboratory Required Qualifications: Qualifications needed for this position include a PhD in clinical psychology or a related field, such as psychology
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Job Description A fully funded postdoctoral position is immediately available Mark Hatley's laboratory in the Molecular Oncology Division of the Department of Oncology at St. Jude Children's
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a postdoctoral scholar in computational biology. The PI, Dr. Lixing Yang is an Associate Professor at the Ben May Department for Cancer Research and the Department of Human Genetics. To learn more
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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understanding and generation, media forensics, anomaly detection, multimodal learning with an emphasis on vision-language models, computer vision applications for space. Key responsabilities: Shape research
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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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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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skills; ability to work independently and collaboratively; willing to and capable of learning new skills needed to complete the research projects. About the lab and St. Jude: Upon completion
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Aarhus University (http://bio.au.dk/en) and work in the Archaea Group (https://bio.au.dk/en/research/research-areas/microbial-processes-and-diversity/archaea-group), Section for Microbiology
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights