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Nonhydrostatic) model. Job description Contribute to the further development of the EXTPAR software Address issues reported by international users on the EXTPAR repository, including consistency checking and
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100%, Zurich, fixed-term The postdoctoral researcher will advance the application of AI, large language models (LLMs), and machine learning to extract trustworthy climate information from large
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abnormal noradrenergic signaling. In close collaboration with the University of Oxford, we combine cutting-edge computational modeling of human behavior with pupillometry and functional magnetic resonance
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As part of the MALOQ project, you will train state-of-the-art ML models to learn atomic, electronic, and vibrational properties of large-scale atomic systems representing the building blocks
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We are seeking an exceptional and highly motivated Postdoctoral Researcher to lead research on the in-hospital deployment of Large Language Models (LLMs). The focus of this position is the
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if they do not meet all the listed requirements. Research shows that this is particularly true for women. If you believe that your profile is a good fit for this position, we invite you to apply even if you do
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examines the cellular and molecular mechanisms that link such conditions to diseases in exposed individuals and their descendants. The lab uses mouse and cellular models and a variety of experimental
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-edge AI/ML projects in a high-performance and data-intensive environment. We value technical excellence, curiosity, and the ability to learn and grow, rather than a initial perfect match of a skills
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-quality research. Strong analytical skills, particularly with in-situ techniques (e.g., EPMA, LA-ICP-MS, SIMS). Experience in field work, geochronology (e.g., U-Pb, Ar-Ar) and/or numerical modelling