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scholarships based on need. Students with the greatest need will receive the highest value scholarships. About the scholarship The Learning Potential Fund provides support through scholarships and bursaries
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. (2017). Beyond prediction: Using big data for policy problems. Science, 355(6324), 483–485. Barocas, S., Hardt, M., & Narayanan, A. (2021). Fairness in Machine Learning. Retrieved from https
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this limitation in the use of satellite observations by make a direct use of radiance observations retrieved by satellites using machine learning without the need of radiative transfer calculations. The new model
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of Applied Engineering is looking for a full-time (100%) doctoral scholarship holder in the field of in-air acoustic sensing and applied machine learning for building the next-generation of intelligent robotic
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posts,PHD Thesis Starting date: 30.10.2025 Job description: DESY Foundation models are multi-dataset and multi-task machine learning methods that once pre-trained can be fine-tuned for a large variety of
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We are recruiting a new fully-funded PhD student to join Dr Daniel Yon’s Uncertainty Lab at the School of Psychological Sciences at Birkbeck, University of London. This post is attached to a recent grant awarded to Dr Yon from the Leverhulme Trust entitled Public Communication and Private...
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University of Stavanger invites applicants for a PhD Fellowship in in molecular modelling and machine learning for improved subsurface utilization, at the Faculty of Science and Technology, Department
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criteria. We allocate scholarships based on need. Students with the greatest need will receive the highest value scholarships. About the scholarship The Learning Potential Fund provides support through
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. Please do not contact us for unsolicited services. Where to apply Website https://www.academictransfer.com/en/jobs/356217/phd-position-machine-learning-m… Requirements Additional Information Website
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look forward to receiving your application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and verifiability for AI systems