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and machine learning based analyses including predictive modeling and real world evidence generation. Basic Qualifications: MS in computer science, biostatistics, biomedical informatics or related field
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NAISS, the National Academic Infrastructure for Supercomputing in Sweden, provides academic users with high-performance computing resources, storage capacity, and data services. NAISS is hosted by
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accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models, including large
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Computational Cost by Machine Learning and DFT-Based Data, Journal of Chemical Theory and Computation, 2024, 20 (16), 7287–7299. Funding category: Contrat doctoral PHD Country: France Where to apply Website https
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Date 1 Sep 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description
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Date 1 Sep 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description
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Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Study of the production of axions and other particles beyond the Standard Model in
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collaboration with diverse communities, researchers, clinicians, and policy experts. You will work alongside a multidisciplinary team and use both qualitative, quantitative and computational modelling methods
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Washington, D.C. Connections working at Johns Hopkins University More Jobs from This Employer https://main.hercjobs.org/jobs/22103428/modeler-x2f-data-scientist-i-x28-epidemiology-x29 Return to Search Results
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models—including myocardial infarction, tachypacing-induced heart failure, and atrial fibrillation—are essential for understanding disease mechanisms and therapeutic targets. The University of Manchester’s