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, or computer science. Documented experience in professional software development. Documented experience or interest in Artificial Intelligence and Machine Learning development, Proficiency in written and oral
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, imaging). Knowledge on AlphaFold for models in structural protein analysis/proteomics AI/ML Applications: Applying machine learning or AI to predict gene function or discover functional relationships from
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higher education credits, or acquired, in some other way within or outside the country, substantially equivalent knowledge We are looking for a PhD student with strong experience in machine learning, deep
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registries and biobanks. The applicant is expected to have a strong computational focus on innovative development and application of novel data-driven methods relying on machine learning, artificial
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analyses and machine learning. Some data for the project already exist, but additional data will be collected from behavioural tests on privately owned pet dogs in Sweden and abroad (Europe). Travel and time
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. Within the project, two PhD students, one at the Department of Computer and Information Science (with computer science, or possibly design or cognitive science as main subject) and one at Tema Technology
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extensive experience with physics-guided modeling; strong interest in time series machine learning and the ambition to learn are what matter most. The results will support safer automation, fewer failure
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research activities. For information about the Department of Physics, see: www.fysik.su.se/english . Project description Subject: Theoretical Physics We invite applications for a PhD position in the theory
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development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Tasks The position is aimed at researchers early in their career
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at Chalmers University of Technology at the end of the previous period, to complete the PhD studies. About SPACER SPACER aims to develop new architectures for porous electrodes to improve the power density and