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may include but are not limited to: algorithm and software development; application or development of computational or statistical methods; data analysis; modeling; statistics and machine learning
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applications for a Postdoctoral Fellow to join the Human Evolutionary and Statistical Genetics (HESG) Lab. The HESG Lab develops statistical and computational methods to understand human population history and
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power systems, network analysis and power flow; - Experience or academic background in machine learning, Graph Neural Networks (GNN)/Grid Foundation Models and/or probabilistic methods and Monte Carlo
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updates that may occur and are applicable. The fellow may also be reimbursed for the amount corresponding to the Voluntary Social Security, in case of adherence to this plan. 11. Selection methods
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learning, large-scale model optimization, and generalization. To explore scalable optimization methods for large-scale, distributed, and multi-node collaborative training. To conduct theoretical analysis
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a focus on Physical Activity and Health related content. You may also teach more broadly exercise physiology, sport and exercise psychology, and/or research methods. You will have a PhD in a related
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high-ranking journals and university presses Strong command of qualitative and/or quantitative comparative methods Field work experience in the MENA Fluency in English Fluency in at least one language of
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methods to explore the design, impact, and public support for equivalent healthy and planet-friendly food marketing policies in the UK. The successful applicant will undertake research using qualitative and
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these methods to address challenges in scientific discovery and precision medicine. We seek highly motivated applicants with a background in one or more of the following areas: agentic AI, geometric deep learning
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with both academic and industrial partners, and the doctoral candidate must participate in these activities. Methods will include synthetic medicinal chemistry, chromatography, spectroscopic and