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We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training costs and energy requirements of state-of-the-art deep learning models significantly, while...
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Research Assistant to investigate digital reading comprehension through large-scale data analysis. This role, funded by the John Fell Fund, sits at the fascinating intersection of computational
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(FAS) is the historic heart of Harvard University. It is the home of Harvard’s undergraduate program (Harvard College, founded in 1636) as well as all of Harvard’s Ph.D. programs (the Harvard Kenneth C
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technology development. Why become a KTP Associate? The KTP programme is designed to accelerate your career, expand your skills, and grow your professional network. You will have the opportunity to: Work on a
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) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and
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(or equivalent score) both for the programme in total and the master’s thesis See admission requirements: PhD in Science of Professions It is assumed that the person who is hired is admitted to the faculty’s
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compensation plan: tax advantages contracting some products (health insurance, childcare, training, among others.) Training activities: languages, mentoring programme, wellbeing programme. International
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(FAS) is the historic heart of Harvard University. It is the home of Harvard’s undergraduate program (Harvard College, founded in 1636) as well as all of Harvard’s Ph.D. programs (the Harvard Kenneth C
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synchrotron radiation facilities: Primarily at MAX IV (Sweden), but also at ESRF (France), SLS (Switzerland), PETRA III (Germany), and the European XFEL in Germany. The project is computational. The successful
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program. Requirements Very good master's degree in computer science, data science, mathematics or a related discipline; relevant research experience (e.g., master's thesis) in the field of NLP/ML/text