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Postdoctoral Affairs. The FY25 minimum is $76,383. Position is FILLED The Stanford Optima Group is seeking a highly motivated and skilled postdoctoral researcher to lead machine learning projects investigating
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willingness to learn and develop; Teamwork approach, good communication and relational skills; Strong orientation to results, determination, flexibility and aptitude for problem-solving. Furthermore
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considerations. Experience working with machine learning methods for control, perception, or decision-making in physical systems is an advantage. Knowledge of or a passion for sustainable computing
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to science. This is the first large-scale study of its kind, and your results will establish a legacy of scientists working with funding councils to defend their research. Cutting-edge machine learning
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Python is required. Programming in C or C++ is a plus. Background in statistical genomics, longitudinal modeling, non-parametric statistics, machine learning and deep learning are preferred and encouraged
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research focuses on a geometric understanding of training in deep neural networks. The position offers excellent training opportunities at the intersection of machine learning and applied mathematics
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will apply state-of-the-art machine learning algorithms and custom disease-relevant genomic datasets (e.g., coronary artery single-nucleus chromatin accessibility and RNA sequencing) to develop targeted
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, computational, and machine learning/AI methods, with a particular emphasis on deep learning approaches improve our understanding and prediction of infectious disease dynamics. Projects are also strongly grounded
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reasonable cost of living make the greater Bangor area a wonderful place to live. Visit the Maine Office of Tourism to learn more about what the Bangor region has to offer. Qualifications: Required: PhD in
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Postdoctoral Research Associate in Global Environment Modelling of Soil Organic and Inorganic Carbon
. The project is aimed to improve our in-house developed process-based computer model and use it to represent the soil ecohydrological and biogeochemical interactions across various carbon and nitrogen soil pools