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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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; • Familiarity with statistical analyses and modeling as well as machine learning approaches, supported with strong skills in computational optimization of methods; • Experience working with large-scale datasets
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in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy
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The Ho Lab at Yale University School of Medicine (https://medicine.yale.edu/lab/yachiho/ ) is recruiting motivated, productive, independent, and collegial postdocs interested in viral infection, T
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machine learning and concurrent programming will be particularly desirable. You should have a PhD in experimental High Energy Physics and have the potential to be a leader in the field. Experience with
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across a range of application areas, including education and healthcare. As these systems are increasingly deployed in high-stakes environments, there is a growing need for machine learning models
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field. • Experience conducting medical imaging research. • Experience developing artificial intelligence and machine learning approaches for research. • Strong command of statistical methods and their
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-level modelling of environmental exposures and health risks; Interpretable and uncertainty-aware machine learning for heterogeneous health data. This position offers the opportunity to work in a
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application d) Previous experience with computational modelling and machine learning. Additional optional skills and qualifications: Experience with Soft and Living Matter. Contracting requirements
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requirements We will consider applications based on the following skillsets. If you do not fullfil all requirements, please still apply (there is room for learning-on-the-job). A PhD in aerospace/mechanical