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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 3 days ago
YOU MUST APPLY TO THIS POSTING AT THIS APPLICATION SITE ONLY : https://www.utsc.utoronto.ca/webapps/cupehiring/dept/cms/app/sl If you have any issues applying, please contact Kelly Squier
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Dipartimento di Ingegneria dell'Informazione - Università degli Studi di Padova | Italy | 28 days ago
of perceptually relevant features affecting visual quality in multiview content generation systems based on gaussian splatting approaches. • Study of Human Visual System models and user exploration behavior in
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for an Active Ankle Foot Orthosis", Control Engineering Practice, vol. 169, 2026, 106757, doi: https://doi.org/10.1016/j.conengprac.2026.106757 . [4] O. Bey, Y. Amirat, S. Mohammed, "Adaptive Model-Free Control
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Gaussian Splatting algorithms, neural rendering pipelines, and city-scale digital twins. A critical component of this role is leveraging Principal Investigator (PI) status to independently pursue and secure
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the project, a class of moving boundary problems will be investigated. It is assumed that such problems are described by the law for the normal velocity of the interface incorporating mean curvature, Gaussian
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people. By embracing diversity, we believe science can achieve its fullest potential. THE ROLE During your internship you will work on a projectin the Event-Driven Perception for Robotics(https
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conduct research in several areas: analysis of high-dimensional data, Bayesian methods, spatial-temporal models, non-Gaussian modeling, applied research in social science, as well as stochastic models and
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associated with the underlying point processes. The statistical tests will be developed using two types of limit theorems: asymptotic results in the Gaussian regime (central limit theorems) and in the Poisson
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, including sequential Monte Carlo methods, Gaussian processes and Bayesian compressed sensing. Applicants from different backgrounds are encouraged to apply depending on the specific nature of the project
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scene. A particular focus will be on obtaining better models of the noise in EEG data by allowing more realistic heavy-tail distributions instead of the more limited Gaussianity assumptions