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citation record must be focused on AI; or alternatively (B), machine learning engineers with an AI-focused PhD and demonstrated 2-year industry experience in AI development Applicants must have in-depth
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The ideal candidate applies machine learning and big data techniques to important questions in economics, combining advanced computational methods with sound economic theory to uncover insights
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, gender expression, gender identity, genetic information, national origin, race, religion, sex (including pregnancy and pregnancy related conditions), sexual orientation or military status. Duke aspires
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
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the production of polymer latexes that involves a complex, heterogeneous polymerization system and leads to polymers with a diverse range of structures. This project looks to use machine learning to better target
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year of relevant research experiences in similar research role / technical hands-on experience in AI and machine learning Familiarity with large-language models Good written and oral communication skills
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analysis across case study regions. The successful candidate will work on the development and application of AI/Machine learning and behavioural modelling within the North and Baltic seas, utilising legacy
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The role will engage in cutting-edge translational research that develops computational models for predicting outcomes in cardiac diseases. This includes a machine learning model to rule out heart
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Professor (tenure-track) and/or Associate Professor levels with a focus on Data Science and Machine Learning. The expected starting date is summer 2026, with room for flexibility. Depending on the profile
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. The Department of Chemistry and Materials Science is looking for: A Doctoral Researcher (PhD student) in Machine Learning for Surface Structures The Data-driven Atomistic Simulation (DAS) group, led by