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Field
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are looking for highly motivated and talented candidates with a strong background in physics and a fascination for exploring the non-perturbative interaction of light and matter at the ultrashort times
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which you could work in the future. More information about our application process Please send your application only via our online application tool and with the following documents: CV Cover letter
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which you could work in the future. More information about our application process Please send your application only via our online application tool and with the following documents: CV Cover letter
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available in the further tabs (e.g. “Application requirements”). Programme Description The Deutschlandstipendium supports new or advanced students of excellent academic and professional promise. A wide net is
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
learning. It also offers the opportunity to work with data from the European XFEL facility at DESY. Project website Your profile Eligible candidates have strong skills in computational physics and
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. As a model intercomparison project, TIPMIP brings together international modeling groups to jointly develop and run computer simulations. In this way, TIPMIP creates a unique data basis for
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mainly in relation to transformers Experience with Pytorch and transformer architectures is desirable Good English skills Enrolled student (Computer Science, Data Science, Mathematics or similar
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learning, medical image computing, biomedical engineering, medical physics, or related field Strong Python and PyTorch experience Solid publication record and ability to communicate research results
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imaging systems and ensure the optimal deployment and networking of sensors to efficiently process and analyze the resulting data streams. In this way, we support people in decision-making, process
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: A master’s degree in Operations Research, Applied Mathematics, Computer Science, Industrial Engineering, or a related field A solid background in dynamic programming, Markov decision processes