26 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" Postdoctoral research jobs at BIOMEDICAL SCIENCES RESEARCH CENTRE "ALEXANDER FLEMING"
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and engineering optical setups Experience with coherent control of quantum systems Competence in electronics design and hardware control Ability to acquire and process large datasets Enthusiasm
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 months ago
(2018); https://doi.org/10.1063/1.5033338 Shuyan Zhang, Alexander Soibel, Sam A. Keo, Daniel Wilson, Sir. B. Rafol, David Z. Ting, Alan She, Sarath D. Gunapala, and Federico Capasso, “Solid-immersion
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the excellence of the University and to offer our students richly varied disciplines, perspectives, viewpoints, and ways of knowing and learning. Candidates should address how they would contribute to the research
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
Statistics and Data Science Center at the Institute for Data, Systems, and Society is seeking applicants for a Postdoctoral Associate in the general areas of statistical learning, reinforcement learning
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Web Page: https://mathematics.huji.ac.il/
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Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2/ . Related Links: The Center for Quantum Leaps: https
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. Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. Where to apply Website https://academicpositions.com/ad/chalmers-university-of-technology/2026/postdoc
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– forward. URL to this page https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job&rmjob=14530&rmlang=UK
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opportunities within the faculty and beyond in research centers like the Campus Centre of Biodiversity and Sustainable Land Use (CBL) or the Campus Institute Data Science (CIDAS) various opportunities
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• Skilled in single-cell/population data analysis (e.g., GLMs, decoding) Preferred Qualifications • Background in machine learning or computational modeling (Bayesian methods, neural networks, etc