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Post doc position in theory of machine learning at Department of Computer Science, Aarhus University
A post doc position in theory of machine learning is available. The post doc is under the supervision of Professor Kasper Green Larsen, Aarhus University, Denmark. The focus of the research project
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to the study of symmetric computation. The ideal candidate will have a strong background in logic and complexity theory and a desire to apply them to the study of symmetric computation. The successful candidate
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to the study of symmetric computation. The ideal candidate will have a strong background in logic and complexity theory and a desire to apply them to the study of symmetric computation. The successful candidate
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that centres liveability and lived/living experience. More information about our project can be found here https://blogs.ed.ac.uk/discovering-liveability/ . The post requires in-person ethnographic work in an
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an expected starting date in early 2026, in the Cuernavaca branch of the Institute in the state of Morelos, Mexico. UNAM is Mexico's leading university and is home to some of the most prominent research
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, EdD) in education or other relevant discipline and demonstrate excellence in teaching and mentorship at the graduate level. Experience and expertise in health professions education theory and
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agreement (preferably, 2025 Q2) Duration: Yearly contract for 3(+1) years, renewable based on performance and funding availability About the Position The successful candidate will contribute
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an ambitious interdisciplinary cross-institutional team and will be actively contributing to innovative suicide research that centres liveability and lived/living experience. More information about our project
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25 Feb 2025 Job Information Organisation/Company Institute of Nuclear Physics Polish Academy of Sciences Department Department of Particle Theory (NZ42) Research Field Physics Researcher Profile
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We are seeking an applicant for a fully-funded ERC Research Assistant position with the opportunity to undertake PhD studies in statistical methodology and theory led by Professor Richard Samworth