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interface of machine learning, deep learning, data science and applications in forest sciences. Together with the Director, you will further develop KIForst as a faculty-wide platform for methodological
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technical excellence with a deep understanding of sustainable development in shaping societies. Our research focuses on sustainable built environment, mechanics and materials, multidisciplinary energy
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/ Population-scale multiome immune cell atlas reveals complex disease drivers https://www.medrxiv.org/content/10.1101/2025.11.25.25340489v1 A structure-informed deep learning framework for modeling TCR-peptide
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 20 days ago
Demonstrated research experience in machine learning, deep learning, medical image analysis, computer vision, biomedical data science, or a closely related area. Strong programming skills in Python and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
Demonstrated research experience in machine learning, deep learning, medical image analysis, computer vision, biomedical data science, or a closely related area. Strong programming skills in Python and
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learning and physics, addressing key challenges in modern quantitative biology. The successful candidate will be responsible for: • Develop and train deep learning models (CNNs, ...) data to predict IPLSs
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of artificial neuron network have been demonstrated based on single nanomechanical device. The main mission of this postdoc project, financially supported by IMITECH project, is to develop reservoir computing
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as a member of the GHER contributing to the EU research project COMEDI in a consortium of 11 leading partners in the field of data assimilation and deep learning. A successful applicant will develop
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qualifications include: Strong research experience in deep learning and foundation models, including experience with pre-trained models, fine-tuning, transfer learning, or self-supervised learning. Experience with
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systems. For more information, visit https://labs.utsouthwestern.edu/orth-lab About the Role We are seeking an expert structural biologist to join the Orth Lab as a Research Specialist II at UT Southwestern