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Apply online now: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=24712 Postdoc in Bioinformatics Stellenanzeige merken Stellenanzeige teilen wanted for the next
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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
developing scalable machine learning models for applications in materials science. Your tasks include contributing to the development of the Materials Learning Algorithmssoftware package and applying machine
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expertise from a wide range of partners in academia and industry, with both application and system expertise. About us CAPS is part of TUM’s department of Computer Engineering, one of the leading CE
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CW and femtosecond optical spectroscopy methods. Preference will be given to candidates who already have some postdoctoral experience, but applications from recently graduated PhDs with an excellent
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. The researcher will work under the mentorship of Dr. Pascal Geldsetzer and receive a designation as visiting researcher at the Stanford University School of Medicine. Job-ID: V000010072 Field of application
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04.06.2025 Application deadline: 30.06.2025 The Theoretical Particle Physics Group at the Institute for Theoretical Physics at Tübingen University invites applications for the position of a
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interdisciplinary perspectives excellent communication skills in English (both written and oral) a willingness to engage with and learn the programming languages and software tools necessary for the modeling work. We
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Your Job: ...to revolutionize applications of the physical sciences through tailored large language models (LLMs) and intelligent agentic systems. Your tasks in detail: Development and fine-tuning
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Job Offer from June 24, 2025 The Max Planck Institute for Physics invites applications for Postdoctoral position(s) focused on R&D in connection with the Axion Dark Matter search experiment MADMAX
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, computational physics, statistical physics, non-equilibrium quantum many-body physics Ideally, experience with neural quantum states or other applications of machine learning methods in many-body physics