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at cell membranes; Apply machine-learning models trained on simulation data to study how lipid composition and genetic variation influence the conformational and phase properties of membrane-associated
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that you have a PhD in natural sciences/technology/medicine/mathematics/physics or equivalent, with a focus on machine learning, Excellent oral and written English skills, Publications in machine learning
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sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a PhD position at Uppsala University. The Department of Civil and Industrial Engineering consists of three
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look forward to receiving your application! At the intersection between AI and single atoms. Your work assignments We are looking for a PhD student with a background in machine and deep learning with
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, contribute to a better world. We look forward to receiving your application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and
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application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and verifiability for AI systems, based at the Department of Computer
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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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Chemistry (experimental/computational physical chemistry) -Transition metal photocatalysts studied by femtosecond X-ray science with a focus on hybrid experimental/machine-learned structural dynamic analyses
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implications of AI-enabled conversational guides for enhancing visitors’ learning and experiences in public educational environments. The PhD student will focus on addressing the challenge of visual blindness in
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the Higher Education Ordinance. To meet the general entry requirements for doctoral studies, you must: hold a Master’s (second-cycle) degree in engineering physics, electrical engineering, machine learning