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fundamental research, we create widely used open-source software including autodE, cgbind/C3, and mlp-train. Our recent advances in Machine Learning Interatomic Potentials (MLIPs) form the foundation of our ERC
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, including exoplanet studies, machine learning, cutting-edge radio instrumentation and digital signal processing, citizen science, sky surveys, and studies of transient and variable objects. Listen is deeply
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situ advanced microscopy of fibre‑based materials. The project aims to develop and deploy machine learning tools that extract real‑time structural and chemical information, enabling deeper understanding
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VwGr. B1 lit. b (postdoc) Limited until: 31.03.2032 Reference no.: 5336 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support
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imaging datasets and advanced machine learning approaches to identify novel imaging markers of mental health disorders and cognitive function; 2) developing robust MRI-based acquisition, image
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in theory of probability and statistics, machine learning, or formal methods. The post is available from 2 March 2026 until 1 March 2028. If you are still awaiting your PhD to be awarded you will be
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structures unavailable elsewhere. Your role and goals The successful candidate is expected to lead the experimental effort with a team of PhD and master’s students and collaborate closely with theorists in
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programme focused on applying AI‑driven analysis to in situ advanced microscopy of fibre‑based materials. The project aims to develop and deploy machine learning tools that extract real‑time structural and
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outputs, and carry out collaborative projects with colleagues in partner institutions, and research groups. The successful candidate will have completed, or be close to completing, a PhD/DPhil in a relevant
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investigating how dopaminergic and serotonergic systems interact in the primate frontal cortex to support learning and decision making. About the department The Department of Experimental Psychology is a large