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Computational modelling of two-dimensional graphene-based materials School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Natalia Martsinovich Application Deadline
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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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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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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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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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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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Department of Biology Faculty of Science University of Copenhagen The Kresten Lindorff-Larsen group is looking for a PhD student in computational biophysics and machine learning studies
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 7 days ago
the replicator equation. The candidate(s) may also be required to develop computational and algorithmic platforms to link models to biological data. The project integrates dynamical systems, graph theory, linear
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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
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, and modeling of structural heterogeneity in biological macromolecules. Rather than only applying established workflows, you will explore new computational formulations and alternative ways