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Field
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and field experiments, use of naturally occurring (i.e. census) data as well as theory building. Funding for field research and conference visits is available in consultation with the supervisor dr
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) Job description This vacancy is positioned in the section Materializing Futures of the Sustainable Design Engineering Department. The Materializing Futures section focuses on developing theories, tools
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interest in learning, adaptation, and dynamical systems in physical contexts Experience with analytical and\or computational modeling. Proficiency in numerical methods and coding (Python, JAX, MATLAB
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they make about the relationship between theory and practice, and how they handle the distinctive consequences of socially disruptive technologies (including conceptual disruption, uncertainty, and moral
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to address this gap by developing and testing a new neurocognitive theory of spoken language learning that integrates cognitive, sensorimotor, and affective mechanisms. Moving beyond traditional accounts
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project, you will Develop theory and a statistical method to estimate genetic variance components in populations under selection (together with colleagues). Validate the new method using simulations
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mission of unlocking the “geometry of artificial intelligence” then please apply! What you will do Singular Learning Theory (SLT) is a mathematical framework for analysing statistical models that do not
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Institute of Physics that focuses on complex fluids and soft mesoscopic materials, both experimentally and computationally. There are strong links with soft condensed‑matter theory and computational chemistry
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expertise in the philosophy of mathematics and advanced formal skills. Demonstrable expertise in proof theory and provability logic will be an advantage. Your publication record is that of a talented early
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Algebraic Topology. The PhD student will work on topics in Topology such as manifold invariants, exploring links to Homotopy Theory and Mathematical Physics, under the supervision of Renee Hoekzema