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candidate is self-motivated and hard-working with a PhD in Data Science, Computational Social Science, Computer Science, or Information Science. The position requires experience with at least one of the
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phenomenology particular in relation to Higgs, neutrino and BSM physics, and help in supervising PhD students. The appointment would be for two years with the possibility of an additional year. The successful
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University of Gothenburg as principals. The position is placed in the Division for Computer network and systems and the employment is placed with Chalmers University of Technology. Our research spans from
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Fractional Quantum Hall effect remains a largely unsolved problem
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Dec 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Dec 2025 Is the job funded through the EU Research Framework Programme? Horizon 2020 Reference Number BAP
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/requirements We are looking for highly motivated, dedicated, and ambitious candidates with: A PhD in Molecular Biology, Biomedicine, Computational Systems Biology or similar. If you have not yet completed your
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natural language processing and machine learning workflows; (3) experimental design and causal inference (including virtual lab experiments); and/or (4) network or computational modeling. The ideal
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/Administrative Internal Number: 6558697 Postdoctoral Research Associate About the Opportunity The Network Science Institute (NetSI) at Northeastern University is a world-leading center for research and education
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, tensor analysis, and network science to foster the professional development of team members. Qualifications and experience essential PhD in Applied Mathematics in the fields of Numerical Linear Algebra
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, theoretically grounded, and explainable. The research sits at the crossroads of quantum information science, tensor network theory, and generative modeling (transformers, diffusion models, etc.). Key research