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related to modeling and simulation of biological systems, 3) very good IT skills, in particular the ability to program in Python, 4) very good knowledge of machine learning methods, neural networks, and
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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, including health and life insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu
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, including health and life insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu
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. Trains, deploys, and evaluates machine learning models. Uses subject matter and best practices knowledge to perform lab and/or research-related duties and tasks. Works independently to assist with
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Join the Responsible Machine Learning (ML) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research
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University of Science and Technology (NTNU) has a vacant position as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the
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or equivalent experience in machine learning or a related quantitative field (Computer Science, Artificial Intelligence, Statistics, Mathematics, Physics, Computational Biology/Chemistry). Candidates will be
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for the 2027-28 academic year. Qualifications We invite applications from those who hold a PhD (or equivalent) or expect to complete the requirements for a PhD in finance by July 1, 2027 or soon thereafter. (We
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beginning in the 2027-28 academic year. Qualifications We invite applications from those who hold a PhD (or equivalent) in the relevant field(s) or expect to complete the requirements for a PhD in accounting