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. The research is focused on catalysis, molecular recognition, structure and dynamics of complex molecular systems, and relationships between the presence of biomolecules and synthetic chemical compounds
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, PyTorch, and JAX) is a plus; familiarity with one or more of the following concepts: language models, explainable AI, robust ML, causal inference, fairness, active and lifelong learning is a plus, but not
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
solution (NBS) due to their potential to act as carbon sinks and regulate hydrology, thereby mitigating the impacts of climate change. Despite growing recognition of their importance, there remains a lack of
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The successful candidate will be expected to conduct and lead their own experiments whilst also supervising the activities of junior group members and PhD students Responsibilities will also include assistance in
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is committed to building champions through academic achievement, athletic excellence, and national recognition of student-athletes, teams, and programs. We are a proud member of the Southeastern
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projects Contribute to the organisation of local seminars or workshops as necessary Education, Qualifications and Experience The ideal candidate will have the following skills and experience: Essential: Hold
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Date : 14-Jul-2025, 11:59:00 PM Disclosure and Barring Service Requirement: Not Applicable. Working at Durham University A globally outstanding centre of teaching and research excellence, a warm and
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of Biosciences at the University of Sheffield investigating development of the brain. You will work closely with the project team to provide essential support for specific research activities, assist with
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for education and professional development opportunities. Description Fellowship Activities The U.S. Department of Energy (DOE) Science, Technology, and Policy Program is designed to provide opportunities
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on the training strategies. In this project, we will investigate Bayesian methods to train deterministic SNNs (with deterministic activation functions) or probabilistic SNNs. Bayesian deep learning methods have