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recording. The work will also include developing new statistical data analysis tools for behavioral and neural data. More broadly, the postdoc will be part of a large and intellectually vibrant community
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to significantly extend our existing team’s capabilities for data scoring and analysis (e.g., with expertise in natural language processing, machine learning, or computational modeling). Finally, the
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, dimensionality reduction and/or machine learning methods (e.g., Lasso, ridge regression) is highly desirable. Familiarity with neurostimulation, Parkinson’s disease, or neuropsychological assessment tools is
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. To address these challenges, the project proposes a multidisciplinary approach integrating expertise from researchers in machine learning, cybersecurity, knowledge representation, human-computer interaction
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all over the world, we work together to develop solutions for the global challenges of today and tomorrow. Where to apply Website https://academicpositions.com/ad/eth-zurich/2026/postdoc-position-in
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graphs and related structures, limit theorems, stochastic calculus and applications, for example in machine learning and mathematical statistics Participation in the scientific activities of the department
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(iii) complex architectures with tightly coupled components hinder modular adaptation. To address these limitations, we research a physics-guided machine learning framework that integrates physical
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that preserves object identity or style. They should have a solid publication record in top-tier computer vision conferences such as CVPR, ICCV, or ECCV, and demonstrate proficiency in deep learning frameworks
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=KFUbXYYAAAAJ&hl=en https://sites.google.com/site/matejhof/publications/harmonious Orcid 0000-0001-8137-3412 H-index (WOS) 17 Website for additional job details https://www.cvut.cz/en/ctu-global-postdoc
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behavior of these components will be developed based on Finite Element Methods (FEM) complemented by Machine Learning models. Legislation and Regulations: Statute of Scientific Research Fellow, approved by