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leave the car at home; A great opportunity in a specialised hospital where you can also continue to learn and grow yourself if you wish: the AVL Academy offers innovative and inspiring education in
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Engineering, Physics, or a similar field. Preferred Qualifications Strong technical background in one or more of the following areas: signal processing, advanced data analysis, statistics, and machine learning
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-preserving communication The ideal candidate is self-motivated and can work independently, has a passion for security and privacy topics in different application contexts, and is willing to learn new
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow. We welcome you to join our community
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: signal processing, advanced data analysis, statistics, and machine learning – Experience in safe laboratory procedures. Effective verbal and written communication skills. Laboratory experience
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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, and semi-structured interviews. Using European competence models (e.g., GreenComp, LifeComp), the project will develop flexible lifelong learning models that universities can adapt to different
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on public transport we also make it attractive for you to leave the car at home; A great opportunity in a specialised hospital where you can also continue to learn and grow yourself if you wish: the AVL
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Grant, focusing on the development of novel deep learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted
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from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural