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that can be used for training machine learning and deep learning models. You will work in tight collaboration with other researchers in Nijmegen, Delft and at the Hubrecht Institute (van Oudenaarden group
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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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PhD position on Closed-loop testing for faster and better EM evaluation of complex high-tech systems
and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With ICT present in almost every
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and to acquire valuable research experience. The PhD Project Life in the Greek-speaking cities of the Eastern half of the Roman Empire was infused with cultural interactions and the rich and pluralistic
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observations. Your major challenge is in model development, and there is room for you to develop machine learning applications in the field of firn modelling. If successful, your work will lay the foundation
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chemical reaction networks with robotic systems and analytical science. You will also learn how to programme robotic systems and how to implement aspects of deep learning and neural networks for reservoir
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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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learning environments based on pedagogies that promote justice and fairness. To address this need, the Centre for Learning and Teaching (CLT) is offering a fully funded, 4-year PhD. The selected candidate
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Research Group Twente: The research focus of the statistics group is on the development of statistical methodology for new data applications and the theoretical analysis of machine learning methods, in
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. Legal systems worldwide—and particularly within the European Union (EU)—are facing urgent challenges in addressing the ethical and societal impacts of AI-driven applications and machine-learning