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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
performance in core mathematics and machine learning courses Master’s degree (or near completion) corresponding to at least 240 higher education credits in mathematics, computer science, electrical engineering
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the Swedish National Infrastructure for Computing (SNIC) and the Chalmers Centre for Computational Science and Engineering (C3SE). Learn more about the project and the research: Project overview Due
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What does policy and practice for recruitment to university STEM (Science, Technology, Engineering, and Mathematics) education look like, and what are the consequences for equality and social
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28 Feb 2025 Job Information Organisation/Company Chalmers University of Technology Research Field Physics » Computational physics Physics » Mathematical physics Physics » Quantum mechanics
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, Engineering, and Mathematics) education look like, and what are the consequences for equality and social justice? Much research and initiatives to counter inequitable participation in STEM has focused
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: M.Sc. degree (or equivalent) in Physics, Mathematics, Computer Science, or a related field, corresponding to at least 240 higher education credits. Proficiency in conducting literature reviews. Expertise
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of algorithms in general and cryptography in particular Master degree in mathematics, computer science, or a related discipline Fluent in spoken and written English Contract terms Full-time temporary employment
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28 Feb 2025 Job Information Organisation/Company Chalmers University of Technology Research Field Physics » Mathematical physics Physics » Quantum mechanics Physics » Computational physics
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of about 10 percent of full time. Qualifications The applicant should have a Master's degree in Applied Mathematics, Engineering Physics, Electrical Engineering, or equivalent, with excellent knowledge
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. The applicant should have strong background in mathematical foundations of computer science and experience in Python programming. Previous experience in deep learning, reinforcement learning, or explainable AI is