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equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep learning, or signal processing; familiarity with
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Your Job: The PhD project is methodologically independent, with the opportunity to contribute to collaborative efforts at the interface of data science, imaging, and materials research. You will
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to the new theoretical development of graph deep learning, and contribute to the research community of brain connectivity and network neuroscience. This is a joint Phd studentship between Coventry (UK) and
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6th October 2025 Languages English English English The Department of Manufacturing and Civil Engineering , Faculty of Engineering, NTNU, has a vacancy for a Phd Candidate in Deep Learning for Real
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | 7 days ago
enabler of machine learning for eDNA-based assessments of deep-sea ecosystems” (m/f/d) Background Deep-sea ecosystems host highly diverse biological communities that provide key ecosystem functions and
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Ine-Therese Pedersen 15th August 2025 Languages English Norsk Bokmål English English PhD position in Deep Learning for Metocean Data Apply for this job See advertisement About us We are announcing a
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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) before the human eye can see them. The principal aim of this PhD research program is to develop methods to improve the hyperspectral image classification using deep learning techniques. The developed
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and