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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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parametric winglet geometry model. The developed tool is meant to be able to generate winglet shapes, for a given wing planform, using a set of geometric parameters, which can be incorporated in
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incorporate it into mathematical models of trait evolution across phylogenies. The work combines dimensionality reduction and geometric data analysis with the development of statistically rigorous comparative
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fellow in PHYsics-based modelling towards Geometric Algebra Transformers for ISAC. This exciting role will require the successful candidate to develop a physics-informed framework for reconstructing
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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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holographic models, and applying them to shed new light on the physics behind black hole horizons and spacetime singularities. Matrix theory is an important approach to non-perturbative string theory in which
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9 Feb 2026 Job Information Organisation/Company Université Gustave Eiffel Research Field Computer science » Modelling tools Engineering » Electrical engineering Researcher Profile First Stage