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, fluid flow, and solute transport. Develop efficient computational coupling strategies to integrate these physical processes. Apply advanced numerical methods to construct dendrite growth models, including
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AI Singapore (AISG) is Singapore's national programme in artificial intelligence, launched by the National Research Foundation (NRF) to anchor deep national capabilities in AI. Hosted at Nanyang
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Details Title Fellow in AI/ML for Cellular and Protein Computational Biology School Faculty of Arts and Sciences Department/Area Kempner Institute for the Study of Natural and Artificial
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The Associate Biomedical Modeler performs basic pharmacometric modeling and/or statistical analysis to support laboratory and/or clinical research projects. Performs these tasks independently and
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on computer vision. The role will focus on developing, designing, and implementing novel algorithms and models to address emerging problems in computer vision, such as Multimodal Large Language Models and
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positions. Dr. Wei Peng's group (www.weipengenergy.com) focuses on modeling institutional and human dimensions of energy transition to identify realistic and robust decarbonization strategies. The appointment
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(Europe/Rome) Country Italy Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 23 hours ago
uncertainty quantification. The position is supported by a NASA-funded project focused on probabilistic downscaling of global weather models using satellite remote sensing, generative AI models, and conformal
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(Europe/Brussels) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Oct 2026 Is the job funded through the EU Research Framework Programme? Not funded by
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project - “Towards efficient large model training via learning from small model”. He/She will be required to: (a) conduct research on knowledge distillation and transfer learning from small models