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Job Description This position offers a unique opportunity to work on advanced projects at the intersection of AI, machine learning, computer vision, and multimodal learning, focusing on advancing
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The Computational Science Division (CPS) at Argonne National Laboratory (near Chicago, USA) is seeking a postdoctoral researcher to enable exascale atomistic simulations of ferroelectric devices
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methodologies in brain diseases. The candidate will work on developing advanced new algorithms, testing and validation, and applications in these data modalities. The candidate will have the opportunity to work
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 14 days ago
more than 40 research groups and some 1,000 employees from over 50 nations, it is the largest institute of the Max Planck Society . The Department of Theoretical and Computational Biophysics , headed by Prof
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25 Jan 2026 Job Information Organisation/Company CNRS Department Institut de Recherche en Informatique Fondamentale Research Field Computer science Mathematics » Algorithms Researcher Profile First
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7 Feb 2026 Job Information Organisation/Company CNRS Department Institut de Recherche en Informatique de Toulouse Research Field Computer science Mathematics » Algorithms Researcher Profile First
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23 Jan 2026 Job Information Organisation/Company DURHAM UNIVERSITY Research Field Computer science Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application Deadline 11
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/or experience with large-scale data analysis, algorithm development, or computational modeling. Required Qualifications: Doctoral degree in linguistics, cognitive science, psychology, hearing and
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of computational biology, Genomics, machine learning, and data science, contributing to the development and evaluation of advanced algorithms for analyzing large-scale biological datasets. This role is ideal
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advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models