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. To create efficient adjoint-based optimization methods for tunable metasurfaces that provide rapid sensitivity/gradient evaluation, support high-dimensional design spaces, and allow systematic optimization
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requirements, especially for reasoning about complex document collections. We’re building methods to make it easier to tell when LLM outputs can’t be trusted, and to improve systems efficiently from limited
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. Good command of statistical research methods (see methods listed above). Good proficiency in statistical software (e.g., R, Stata). Experience in academic leadership or in supervising postgraduate-level
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artificial intelligence Software engineering Position details Positions are intended for researchers who have recently completed their doctoral degree or who will complete their doctoral degree before starting
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programme under the Marie Skłodowska-Curie Action (MSCA), University of Helsinki is offering a PhD fellowship for a Doctoral Candidate (DC), starting 1 September 2026 or as soon as possible hereafter. A
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of analytical methods, digestion models, dietary modelling, and conducting consumer surveys will form part of the Doctoral Network’s tasks. The 12 PhD candidates will be based across seven different universities
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supervising doctoral students. Join us in shaping the future! Your role and goals Your primary task as a postdoc is to conduct research into various quantum algorithms and optimization methods, both
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programme under the Marie Skłodowska-Curie Action (MSCA), University of Helsinki is offering a PhD fellowship for a Doctoral Candidate (DC), starting 1 September 2026 or as soon as possible hereafter. A
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of analytical methods, digestion models, dietary modelling, and conducting consumer surveys will form part of the Doctoral Network’s tasks. The 12 PhD candidates will be based across seven different universities
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synthesis methods for the Abstraction and Reasoning Corpus (ARC) challenge . ARC is a benchmark designed to measure an AI system's ability to efficiently acquire new skills outside its training data