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outstanding candidates to apply for a postdoctoral research position in Geometric Deep Learning, with a strong emphasis on applications to biology and scientific discovery. This unique research collaboration
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Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based on autofluorescence (AF) imaging
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2025. We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based
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, Gaussian processes, discrete probability, extremal combinatorics Zlil Sela Geometric group theory, Model theory Ari Shnidman Number theory, arithmetic geometry, automorphic forms Evgeny Strahov Random
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foundational and applied topics in computer vision and machine learning, with particular strengths in inverse problems, generative models, and geometric deep learning. We work across diverse application areas
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, geometric modelling, acoustic signal propagation, Monte Carlo simulation methods, decision theory, uncertainty quantification, machine learning. Applications and areas of key innovation Image analysis
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, sensing techniques, optimisation theory and algorithms, multi-modal data processing, high-performance computing, mathematical image analysis, geometric modelling, acoustic signal propagation, Monte Carlo
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in innovative research that includes: Geometric Control Algorithms: Develop and refine control strategies utilizing differential geometric methods, particularly Riemannian manifolds, to optimize robot
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 2 months ago
Description Two Postdoctoral Positions at The University of British Columbia Department: Mathematics (A) Postdoctoral research fellow in mathematical modelling and control theory in sustainable fisheries
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, scipy, scikit-learn, pytorch, pytorch geometric, etc.). Proficiency in statistics and graph machine learning, including the ability to build and deploy models, and evaluate their performance. Software