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Field
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(HPC) and scalable AI pipelines Development of reproducible software tools and computational workflows for biomedical research Develop novel AI, machine learning, and deep learning methods to address
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development of machine learning techniques that may be used to triage, classify, and otherwise process material of a distressing nature (such as child exploitation material). It will involve the use of deep
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development of machine learning techniques that may be used to triage, classify, and otherwise process material of a distressing nature (such as child exploitation material). It will involve the use of deep
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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qualifications: Strong background within machine learning/deep learning, and immunoinformatics is a requirement Knowledge of structural biology and protein structure modeling is a plus Knowledge of the basic
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Details Title Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI School Harvard T.H. Chan School of Public Health Department/Area Biostatistics Position Description The
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 18 hours ago
, machine/deep learning or closely related fields. The candidate must have completed all Ph.D. requirements by commencement of the appointment and be within 5 years of completion of the Ph.D. Minimum
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 18 hours ago
machine learning, deep learning and computer vision (3) Experience in CCUS modeling with numerical reservoir simulators such as CMG, Eclipse, MRST or TOUGH-React (4) Experience in inverse modeling
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply