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exciting opportunities for machine learning to address outstanding biological questions. The postdoc to be recruited will be working on the development of machine learning methods for single-cell data. In
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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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(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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, and written communication skills evidenced by a publication record in the area of control theory, mathematical optimization, AI, or machine learning. Preferred Qualifications: Publication record in
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, France [map ] Subject Areas: Machine Learning / Machine Learning Statistics Mathematics Probability Statistical Physics Appl Deadline: 2025/12/20 11:59PM (posted 2025/11/25, listed until 2026/05/25
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interests in applied statistics, machine learning, or computational biology are encouraged to apply. For more information, please visit our website https://ds.dfci.harvard.edu/postdocs to view the list
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-off companies. CONTEXT AND MISSION We are seeking a postdoc to join the Quantum Machine Learning team (QML-CVC) in beautiful Barcelona. The QML-CVC team (https://qml.cvc.uab.es /) is part of
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data from existing cohorts and national registries, applying novel machine learning methods. The specific work tasks will include data management of large studies, scientific work related to the topics