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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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comparative data by fitting Ornstein–Uhlenbeck models with stepwise AIC. Methods in Ecology and Evolution. Klingenberg, C. P. (2016). Analyzing fluctuating asymmetry with geometric morphometrics: concepts
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with mathematical modeling and comfort with formal reasoning across algebraic, geometric, and analytic frameworks. A deep foundation in linear algebra, tensor calculus, and functional analysis; and the
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-Reflective Sensor Oculography (PSOG), addressing calibration and cross-user generalization challenges through the use of hypernetworks. PSOG signals are highly sensitive to geometric, anatomical, and
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working in geometric analysis, mathematical physics, partial differential equations and probability, with whom the candidates will be able to interact. Complete applications should include a detailed
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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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. Specific Requirements Knowledge: Interoperability with IFC formats. Digital Twins. Evaluation of the geometric and semantic representation of the models. Relational databases. Professional Experience: As a
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of manufactured parts, particularly in terms of geometrical accuracy, microstructural control, and mechanical performance. This PhD project aims to develop a Multiphysics model and simulation to gain in-depth
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Omer Ben-Neria Logic, set theory Shai Evra Graph theory, representation theory, number theory Adi Glucksam Complex analysis, potential theory, and dynamics Or Hershkovits Geometric analysis
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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