373 machine-learning "https:" "https:" "https:" "https:" "U.S" Postdoctoral positions in United Kingdom
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support: 0161 850 2004 https://jobseekersupport.jobtrain.co.uk/support/home This vacancy will close for applications at midnight on the closing date. Please see the link below for the Further Particulars
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researchers in applied mathematics and machine learning. This is due to its remarkable flexibility, mathematical elegance, and as it has produced state-of-the-art results in many applications. As a leading
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50 Faculty of Life Sciences Startdate: 01.01.2026 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: permanent Reference no.: 5000 Explore and teach
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signal processing schemes using machine learning methods and knowledge of inverse scattering methods (nonlinear Fourier transform). About us: AiPT is one of the world’s leading photonics research centres
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mathematics or a related field. The successful candidate will have expertise in at least in one of: Machine learning in the context of physical systems AI-based condition monitoring Reinforcement learning
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, please contact Professor Keith Channon: keith.channon@cardiov.ox.ac.uk or cvm_personnel@cardiov.ox.ac.uk. For more information about working at the Department, see https://www.rdm.ox.ac.uk/ The University
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information please visit: https://www.gov.uk/skilled-worker-visa. As a valued member of our team, you can expect: 1 A warm welcoming and engaging organisational culture, where your talents are developed and
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. The salary scale is 3 500–4 000 € per month, depending on the candidate’s experience and merits. Please read more why you should choose the University of Helsinki as your next place to work: https
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Formstone (see Panousopoulou et al. J. Cell Sci. 2016 (https://doi.org/10.1242/jcs.180703) and Prof. Philippa Francis-West (Mao et al. Nature Comms. 2016 (https://doi: 10.1038/ncomms11469 and Prof. Philippa
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capabilities o Demonstrated experience with machine learning and/or statistical modeling o Expertise in handling large-scale, complex datasets with strong data wrangling skills o Strong publication record