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Field
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the context of precision psychiatry, in the Department of Applied Mathematics and Theoretical Physics. The successful candidate will join the team of Dr. Gamze Gursoy, working on topics related to statistical
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mathematics. It hosts activities of two second-year masters, which represent around one hundred students. Its areas of research cover analysis, modeling, and high-performance scientific computing for a variety
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for the study of intraneuronal transport in vivo in animal models such as zebrafish, in collaboration with INRAE. This will be possible thanks to infrared illumination, which provides access to a window of
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mathematics/statistics/computer science, willing to specialize their research on large language models (LLMs). The successful candidate will contribute to the development of trustworthy LLMs by focusing
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Mathematics » Applied mathematics Researcher Profile Recognised Researcher (R2) Application Deadline 28 Feb 2026 - 22:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded
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, or a related field experience in mathematical modelling and scientific programming excellent written and spoken English communication skills As a formal qualification, you must hold a PhD degree (or
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researcher will conduct collaborative research between the Center on Stochastic Modeling, Optimization, & Statistics (COSMOS, https://cosmos.uta.edu/ ) and the Department of Chemistry and Biochemistry (CHEM
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these areas. Ability to work independently on a day-to-day basis. Demonstrated interpersonal, oral, and written communication. Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and
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that incorporates a broad range of neutrino and dark-matter models, assessing their effects on large-scale-structure (LSS) statistics as measured by the power spectrum and bispectrum of galaxies or intensity maps
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Postdoctoral Research position supports advanced research in artificial intelligence, energyefficient computing, foundational mathematical models, high-performance computing, dimensionality reduction, and