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240 higher education credits in Applied Mathematics, Applied Physics, Electrical Engineering, Mechanical Engineering, or a related field. A strong mathematical foundation and excellent academic
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qualifications: To be eligible for this position, you must have (or be close to completing) a Master’s degree corresponding to at least 240 higher education credits in Applied Mathematics, Applied Physics
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
. This PhD project aims to close that gap by developing a rigorous mathematical framework to analyze and explain transformers using information-theoretic tools. You will be co-supervised by: Research
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technology, or applied mathematics, with a specialization in energy systems analysis, or energy economics. Strong written and verbal communication skills in English. The following experience will strengthen
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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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. 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