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, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to collaborating with researchers from other disciplines. The successful candidate will
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efficient peptide catalysts for powerful C-C-bond forming reactions. (2) Prof. Francesca Grisoni (https://molecularmachinelearning.com/ ) leads the Molecular Machine Learning Group at the Technical University
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background in cosmology, astrophysics, physics, mathematics and/or computer sciences, who seek to obtain a Joint-PhD degree from the University of Groningen and Tartu Observatory. To be eligible to apply, a
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the PhD candidate may include (non-)linear inverse load estimation and data-driven/machine learning techniques that rely on physics-informed guidance for improved robustness. A key task will be to quantify
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Uppsala University, we are announcing the position as DDLS PhD student in Data driven epidemiology and biology of infection. Data driven epidemiology and biology of infection covers research that will
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, engineering physics, biomedicine, or similar Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics Specific knowledge of big
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machine learning, engineering, data sciences, applied mathematics, or another related field; or Have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including
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. - Neural networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In
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band score of at least 6.5, internet. TOEFL test (TOEFL-iBT) showing a score of at least 90, or a Cambridge CAE-C (CPE). For additional information, please contact Prof. Dr. Erik Koffijberg
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, business school scientists, system modeling and optimization researchers, computer scientists, legal experts and social scientists working on energy topics. Description of the PhD project The project