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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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employeeship and offers safe, favourable working conditions? We welcome you to apply for a PhD position at the Department of Information Technology, Uppsala University. The Department of Information Technology
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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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student will be involved in is led by Associate Professor Moa Bursell, who will also serve as the main supervisor for the PhD student. The Wallenberg AI, Autonomous Systems and Software Program – Humanity
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educational programs in Computing Science, we are now seeking a PhD student with a focus on Computer Security. The Department of Computing Science has been growing rapidly in recent years, with a focus on
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and small, contribute to a better world. We look forward to receiving your application! Your work assignments We are looking for one PhD student working on generative AI/machine learning, with
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application! Your work assignments We are looking for one PhD student working on generative AI/machine learning, with applications towards materials science. Generative machine learning models have emerged as a
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sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a PhD position at the Department of Information Technology, Uppsala University. The Department
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understanding insect neurobiology that provides proven circuit designs to solve significant problems such as autonomous navigation; Advanced III-V semiconductor nanowire technology that exploits light to obtain a
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streamlining serial crystallography methods To be successful in this role you need to have the following qualifications PhD or equivalent in Structural Biology, Physics, Chemistry, or another field relevant