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expansion project. All applicants whose work would contribute to advancing biological knowledge through machine learning or other quantitative/computational methods are encouraged to apply, including those
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a wide array of family-friendly and cultural programs to eligible team members. Learn more at: https://hr.duke.edu/benefits/ Equal Opportunity Employer: Duke is an Equal Opportunity Employer
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doctoral degree. More about being a doctoral student at LTH on lth.se. https://www.lth.se/english/study-at-lth/phd-studies/ AEGIS — Adaptive Grid-Interactive Edge Datacenter Fleets is a European Marie
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machine learning and AI acceleration. Perform performance, power, and area (PPA) analysis of processor and accelerator designs. Publish research findings in top-tier conferences and journals and contribute
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to topics such as natural language processing and machine learning; computational social science; human-AI collaboration and societal impacts of AI; or AI safety, governance, policy, and cybersecurity. All
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equivalent foreign degree, obtained within the last three years prior to the application deadline Experience with simulation frameworks, system-level performance evaluation, or machine learning, is highly
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Machine Learning within the School of Medicine at the University of Limerick. This is a methodologically focused PhD for candidates with strong quantitative backgrounds who wish to develop novel statistical
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machine learning algorithms to support the traceability of the beef’s geographical origin. She/he will participate in all stages of the project, including planning and supervision of sample collection and
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
for the position. Preferred selection criteria Experience with machine learning or other relevant AI technologies Scandinavian language skills Previous experience from industry or research in engineer-to-order
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worldwide. We host a vibrant doctoral training programme in Science, Technology and Innovation Policy (STIP), currently comprising around 28 PhD students across all cohorts. The Institute and Division also