145 computer-vision-and-machine-learning PhD positions at University of Groningen in Netherlands
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report results via peer-reviewed publications, conference presentations, and ultimately a PhD thesis. The PhD thesis has to be completed within four years. Being part of a cutting-edge research programme
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adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases and in particular the complications encountered in photometric
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four years. Being part of a cutting-edge research programme, you will receive research training as well as a varied educational training program including transferable skills and future (academic or non
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for this position will have the following qualifications/qualities An MSc degree in chemistry or a related field. Very strong academic performance. Experience in molecular machine learning. Experience with
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chemistry or a related field. Very strong academic performance. Experience in molecular machine learning. Experience with the programming language Python. Experience in computational chemistry. Basic
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researcher will receive a tailor-made programme from the GSCF. The PhD candidate is expected to teach a maximum of 350 hours per year The PhD candidate is expected to teach during the first and second year of
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interest in experimental testing, data processing, and machine learning. Organization The University of Groningen is a research university with a global outlook, deeply rooted in Groningen, City of Talent
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processing, and machine learning. Organization The University of Groningen is a research university with a global outlook, deeply rooted in Groningen, City of Talent. Quality has been our top priority for over
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, machine learning, and latest state-of-the-art biochemical analysis tools. You will explore how active enzymes drive cytoplasmic motion and how this influences cellular function and life itself. This is a
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vision on the structure of the PhD and will have the freedom to reshape the research projects within the general boundaries of the subject of spatial and foraging ecology and habitat use of Black-tailed