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Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and
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events (e.g. in the context of ALICES) Participate in the wider academic community through conference and workshop participation Teach and assist in undergraduate and graduate courses Publish research
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analysis (R, Python) is an asset. Curiosity, creativity, rigor, willingness to learn, team spirit and collaborative capacity, excellent time and priority management. Fluency in English (written and spoken
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education team while being affiliated with the Institute for Teaching and Learning and situated within the Department of Education and Social Work (DESW). The position includes organizing and coteaching
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proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C++). Prior proven experience in data-driven innovation projects is
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curiosity, innovation and entrepreneurship in all areas Personalized learning programme to foster our staff’s soft and technical skills Multicultural and international work environment with more than 50
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framework to bridge this gap and enable organizations to confidently deploy secure GenAI solutions by evaluating the machine-learning models intrinsically, identifying components of an AI pipeline and their
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conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities, and Machine Learning/AI 5G on organisations from both the private and public sectors
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. This comprises learning to set up and operate our new optical cryostat platform, which involves advanced confocal microscopy, laser pulse shaping, and time-bin interferometry. (b) You will benefit from our
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and