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Postdoctoral Researcher – Ontology and Knowledge Graph Engineering, you will be contributing to the ongoing development of a general and interoperable modular architecture to build federations of simulation
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Your profile Candidates should have an exceptional academic record and a robust mathematical foundation. They should have published works at the main conferences in the field of machine learning, such as ICML, NeurIPS, ICLR, etc. Excellent communication skills and fluency in English (spoken and...
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phenomenological and quantitative first-principles theory of static and dynamic chirality in crystalline materials. The specific sub-project advertised here seeks to understand the unexpectedly large measured
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areas like programming languages, algorithms, and theory. INSAIT is structured similarly to top U.S. and European research institutions and provides exceptional working conditions, in terms of facilities
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quantitative first-principles theory of static and dynamic chirality in crystalline materials. The specific sub-project advertised here seeks to understand the unexpectedly large measured magnetic moments
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, invites applications for a Postdoc position. This position offers a unique opportunity to engage in research aimed at addressing contemporary challenges in management and organizational theory. Job
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Description The Chair of Number Theory at the Ecole Polytechnique Fédérale de Lausanne (EPFL) invites applications for one or more postdoctoral researcher positions. We seek outstanding candidates working in
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or interest in field theory and astroparticle physics is desirable. Candidates should be able to work both independently and collaboratively and contribute to the positive research group environment
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sciences. It is also a central institution in Switzerland for the theory and practice of digital humanities and offers a master's degree and a doctorate in digital humanities. It has collaborative ties with
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learning (RL), such as (but not limited to) Theory of online learning, reinforcement learning, and data-driven control Learning in games, and multi-agent RL RLHF and alignment in LLMs Representation learning