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/ TensorFlow / Scikit Learn Highly knowledgeable in mathematical and statistical concepts Solid foundation in mathematics for Machine Learning (Linear Algebra, Probability, Optimization). Proficient in English
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complete, a master’s degree in computer science, mathematics, statistics, IT, engineering, biotechnology, bioinformatics, economics, or a related field. Experience with programming in Linux environments
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, conducting theory-driven statistical analyses of longitudinal register data, and, where relevant, linking these with existing survey data. The PhD student will contribute to international journal publications
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Job Description Are you passionate about using experimental physics and mathematical methods to accelerate the green transition and address climate change? Do you want to transform the way we
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environments This PhD project investigates the use of digital technologies (environmental sensing, user feedback loops, computer vision, machine learning) and theories of human perception and behavioral nudging
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in the group of Niels Engholm Henriksen (https://www.kemi.dtu.dk/english/research/physical-chemistry ). You must have a solid foundation and interests in quantum chemistry, applied mathematics
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digital twins to replace hands-on training? Do you want to engage in a career within didactics of STEM (Science, Technology, Engineering and Mathematics) education? This PhD project is a part of the ACCESS
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. Multi-scale computational modelling and large deformation theory. This project also involves a research stay abroad in one of our collaborating groups at Johns Hopkins or Cornell Universities
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in computer science or applied mathematics and a strong interest in electrochemistry, molecular modeling, and sustainable energy technologies. Experience with computational methods, data analysis
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in Demography, Social Science, Economics, Mathematics and Economics, Public Health, Statistics or similar. Furthermore, we expect applicants to: Have strong English skills, both spoken and written. Be