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for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
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conditions and policy outcomes. Desired areas of expertise include: dynamic and complex systems, agent-based modeling, computer programming (familiarity with R, Python, Netlogo), statistical analysis
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and expanding team. You’ll play a key role in our success through your code, publications, and strategic promotion of our work. * PhD in Computer Science, Biomedical Informatics, Machine Learning
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, Effects, and Criticality Analysis (FMECA), functional FMECA, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault
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Details Title Postdoctoral Fellow in On-Premise Computing for Autonomous Vehicles (Computer Architecture, Machine Learning and Runtime Systems) School Harvard John A. Paulson School of Engineering
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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Machine Learning (OxCSML) research group, with responsibility for leading and carrying out research pertinent to the project, as well as day-to-day management of research activities relevant to the project
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Signal Processing and Image Analysis group (DSB), Section for Machine Learning, at IFI. DSB has seven full-time and five adjunct positions and carries out research across image analysis and machine
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nonstationarity, graph theory, machine learning and multivariate statistics; with applications in neuroscience, climate research, economics and general communication networks. More information about the group
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questions and data of CREATE. The successful candidate will conduct advanced methodological and psychometric research. Potential topics include (a) AI, machine learning, and large language models