261 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" positions in Czech
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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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description The project will use bioinformatic analysis together with comparative approaches to individual cells, and machine learning to investigate how the vertebrate head evolved and what mechanisms control
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announces an open competition for the position Ph.D. student - Machine learning-based tools for multiparametric enzyme optimisation Workplace: RECETOX, Faculty of Science, Masaryk University in Brno, Czech
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, or related fields Theoretical and experimental knowledge in the field of wave and geometric optics Interdisciplinary focus, ability to quickly acquire new knowledge and skills, communication with colleagues
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and many other benefits: https://www.tul.cz/univerzita/uredni-deska/kariera/benefity How to log in please send the documents requested below to the following e-mail address: volnamista@tul.cz by
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antibodies and anti-CD20 CAR T-cells form the backbone of treatment for mature B cell malignancies. The project focuses on elucidating changes in gene expression within the tumor microenvironment of chronic
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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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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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animals and humans, contacts with the environment are not avoided and sometimes even actively sought. We will deploy this inspiration from biology to design truly robust machines with distributed control
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will be integrated with statistical and machine-learning methods to classify polarity states and identify quantitative signatures predictive of metastatic behavior. The project will deliver transferable