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You will receive project-specific training in numerical modelling tools and techniques and in machine learning. Eligibility requirements If you have received a First-class Honours degree, or a 2:1
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, or even months to derive a suitable hardware model. This limitation is only exaggerated when considering the digital representation of multicore computer systems, requiring the modelling of a broad range of
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of the future, striving to improve healthcare and society as a whole. Where to apply Website https://www.academictransfer.com/en/jobs/356668/phd-in-machine-learning-for-dru… Requirements Specific Requirements
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using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts generated in the scattering
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for representing and combining multimodal information over time. Grounded in machine learning, representation learning, and efficient algorithms, the work addresses real-world challenges in sustainable and
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that you will help us to build the sustainable companies and societies of the future. The Machine Learning Group at Luleå University of Technology seeks a doctoral student in machine learning. We offer well
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At the Technical Faculty of IT and Design, Department of Sustainability and Planning, a position as a PhD student in Problem-Based Learning (PBL) and Sustainable Education at the Aalborg Centre
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in a field related to one of the three research areas of MCML: Foundations of Machine Learning; Perception, Vision, and NLP; and Domain-Specific Machine Learning. The Munich Center for Machine
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Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy | Austria | 2 months ago
, startups and patient partners. Your Mission as PhD is to develop novel machine-learning methods to (1) detect small, clinically meaningful changes in joints, (2) enable robust longitudinal monitoring and
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with machine learning. Self-Driving Laboratories (SDLs) are emerging research environments where experiments are planned, executed, and analyzed in closed-loop workflows that combine automated