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Joint degree / double degree programme No Description/content Data Science is a scientific field that has emerged at the interface of computer science, mathematics, statistics and applications. It is
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appropriate statistical testing to test the efficacy of the models. The project forms part of a wider effort for developing an effective VR HRI toolkit for improving interactive fluidity between robots and
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, dynamical systems and statistical physics. The candidate will be jointly supervised by the Coventry team Dr Fei He and the Stellenbosch team Prof. Francesco Petruccione . This project will contribute
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The Child and adolescent Health Impacts of Learning Indoor environments under net zero (CHILI) Hub is a program funded by the MRC and NIHR, the goal of which is to understand the health effects we
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University of Veterinary Medicine Hannover • | Hannover, Niedersachsen | Germany | about 2 hours ago
Degree PhD or (if applicable) Dr rer nat Course location Hannover Teaching language English Languages English (100%) Full-time / part-time full-time Programme duration 6 semesters Beginning Winter
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outstanding students from all over the world to apply for PhD positions in our renowned PhD program. Based in Hamburg, our program offers excellent training and top-level structured supervision in climate
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University of California, Los Angeles | Los Angeles, California | United States | about 14 hours ago
Skip to main content Recruit Home Open Recruitments Visiting Researcher (JPF10537) Visiting Researcher Apply now to Visiting Researcher Job #JPF10537 Computer Science / Henry Samueli School Engr & Ap
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, Pennsylvania 19004, United States of America [map ] Subject Areas: Industrial Engineering Economics Mathematics Statistics Management Science & Engineering (more...) Computer Science and Electrical Engineering
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, such as engineering, physics, statistics, or mathematics (minimum requirement is a four-year Bachelor’s degree with honours) The research area The AITHYRA-CeMM PhD Program will focus on the thematic areas
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application