274 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" research jobs in Denmark
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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of Medical Sciences. Further information on the Department can be found at https://www1.bio.ku.dk/ Inquiries about the position can be made to Peter Brodersen (pbrodersen@bio.ku.dk). The position is open from
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. The faculty has an annual budget of DKK 3 billion. Learn more about The Faculty of Science at www.science.ku.dk You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/ .
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at the top venues of machine learning research. Responsibilities and qualifications You should have prior experience with machine learning from both a theoretical and practical perspective. Experience in one
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environment to its 37,000 students (FTEs) and 8.700 employees and has an annual revenue of EUR 1.106 billion. Learn more at www.international.au.dk/ Where to apply Website https://AU.emply.net/recruitment
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within Mathematics. The positions have 1st September 2026 as earliest possible start dates. There are postdoc positions available in the areas listed here: https://math.au.dk/en/about/vacancies/postdoc
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. Qualifications Applicants must hold a PhD or equivalent qualifications in a relevant field, such as Child-Computer Interaction, Human-Computer Interaction, Learning Sciences, Educational Technology, Computer
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. Qualifications Applicants must hold a PhD or equivalent qualifications in a relevant field, such as Child–Computer Interaction, Human–Computer Interaction, Learning Sciences, Educational Technology, Computer
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and teaching environment to its 37,000 students (FTEs) and 8.700 employees and has an annual revenue of EUR 1.106 billion. Learn more at www.international.au.dk/ Where to apply Website https
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). Strong background in stochastic optimization, machine learning, or mathematical statistics. Track record of publications in relevant journals/conferences (ICML,NeurIPS,ICLR,COLT, Siam Journals, JMLR, COAP