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Postdoctoral position in machine learning for the development of novel semiconductor materials Login and apply Lund University Lund University was founded in 1666 and is repeatedly ranked among the
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Description We have an opening for a Postdoctoral Researcher to contribute to experimental heavy-ion physics, detector development, and scientific machine learning within Lawrence Livermore National
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Computer programming skills Desired Qualifications Experience developing computational tools for biomolecular systems Experience training machine learning models Experience working in a collaborative
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Quantitative Finance at EPFL seeks postdocs to reinforce our research in quantitative finance with a focus on applied machine learning. Main duties and responsibilities Working and collaborating on research
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data-intensive physics with nuclear/particle aspects, advanced detector R&D, machine learning and AI and emerging computational methods in quantum computing. The position is intended for an excellent
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AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences | Vienna, Virginia | United States | about 2 months ago
- 72.000 EUR (please see "What we offer" in the job description). Closing date 15 Sep 2026 Website https://www.aithyra.at/ View more categories View less categories Discipline Biomedicine , Computing
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Materials Design and Innovation Posting Number R260134 Posting Link https://www.ubjobs.buffalo.edu/postings/64174 Employer Research Foundation Position Type RF Professional Job Type Full-Time
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. Applications area includes but not limited to multimodal SciML models and deep surrogates for various simulations. This position will be in the Machine Intelligence Group in the Center for Applied
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equipment, and fees associated with manuscript publications, if applicable. A summary of benefits associated with this title/rank can be found at https://hr.uw.edu/benefits/wp-content/uploads/sites/3
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autonomous, closed-loop (“self-driving”) laboratory workflows. The role integrates catalyst synthesis, high-throughput reactor testing, and in situ/operando characterization with machine-learning and