107 learning-"https:"-"Ikerbasque---Basque-Foundation-for-Science" PhD positions in Netherlands
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- Eindhoven University of Technology (TU/e)
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at the University of Twente is looking for two PhD candidates to join the research team of Dr. Gaurav Rattan. The positions are funded by the NWO VIDI project Learning on Graphs: Symmetry Meets Structure (LOGSMS
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this. Implement and test such a framework, in a clinical setting. Help teach explainable AI to bachelor’s students and master's students and/or decision makers. For example, by developing workshops and training
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industrial partners across Europe Network-wide training schools and workshops Supervision by leading experts in the field A personalized Career Development Plan Challenge-based learning principles Where
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interested in using AI to unravel the mysteries of the brain? Do you want to perform cutting-edge NeuroAI research and leverage deep learning to understand human vision? Then check out the vacancy below and
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emerging field with your insights. You will learn how to design chemical reaction networks at material interfaces and become a forerunner in chemically-programmable coatings. Briefly, the core objective of
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, and behavioral intervention using both quantitative and qualitative approaches, including field studies and stakeholder participation. More information can be found here https
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is made for you! Information We invite highly motivated students with a strong background in mathematical control theory, and a keen interest in machine learning to apply for the PhD position within
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secondments in the UK, with DSD families to translate knowledge into patient tools. and with SDM registries. Where to apply Website https://www.academictransfer.com/en/jobs/358126/phd-in-msca-network-studying
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Description This PhD position explores how AI agents can play games to generate meaningful gameplay data. You will work on reinforcement learning, automated feature engineering, and the comparison of AI- and
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-learning (ML)- driven and physics-based computational workflows to screen large molecular libraries, predict key electrochemical and physicochemical properties, and deliver ranked shortlists of high[1