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ATLAS group with a focus on physics analysis and artificial intelligence/machine learning (AI/ML). The successful candidate will contribute to the group’s broad physics program, which includes precision
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, military status, national origin, pregnancy, race, religion, sex, sexual orientation, or veteran status. Final candidates are subject to successful completion of a background check. Additional Information
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expertise is required in categorical data analysis, longitudinal data analysis, and risk modeling using statistical and machine learning approaches. Experience with supervising and managing clinical research
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Functional Theory (DFT), machine-learned force fields (MLFF), graph neural networks (GNNs), or large language models (LLMs). Extensive Knowledge In: • First-principles atomistic simulations with packages
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The applicant must: hold a PhD in a relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have
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computational fluid dynamics (CFD) and computer-aided design (CAD) software. They should also be prepared to engage in both computational analysis and experimental testing as required. Essential criteria
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and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in
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Science About the project This PhD project integrates pharmacoepidemiology, causal inference, and machine learning to study real-world treatment patterns, effectiveness, and safety of monoclonal antibodies
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, artificial intelligence—and particularly machine learning methods—has become indispensable. Depending on the specialty, processed data may include numerical values, point clouds, text or images, often
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practices” research themes. The successful candidate will have: a PhD in Translation Studies/Machine Translation; practical experience conducting data-driven research in a machine translation/large language