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will join a research group working on longitudinal models of multiple chronic diseases across the life course. The postdoctoral researcher will contribute to building and evaluating machine learning
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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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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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machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a biological reference point for identifying disease-specific biomarkers. A central part of the
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perspectives across a variety of domains and complement existing strengths within these departments in bioinformatics, artificial intelligence and machine learning, and expand cutting-edge initiatives including
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. (2) Prof. Francesca Grisoni (https://molecularmachinelearning.com/ ) leads the Molecular Machine Learning Group at the Technical University Eindhoven and will lead a project on designing potent cyclic
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the Faculty of Information Technology and Electrical Engineering . Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/308322/phd-candidate-in-empirica… Requirements Research FieldComputer
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prepared for changes to your work duties after employment. Required selection criteria You must meet the requirements for admission to the Doctoral Programme in Computer Scienc e, see Section 6-1 of the PhD
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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