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future. Fuelled by curiosity and a deep sense of responsibility, they provide invaluable contributions to research and teaching, thus enriching our society. Are you also inspired and driven by the desire
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? Please apply no later than 18 January 2026 via the application button and upload the … Where to apply Website https://www.academictransfer.com/en/jobs/356797/phd-position-in-deep-learning-f… Requirements
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Your Job: We are looking for a PhD student to develop learning-based surrogate models for predicting stress fields in patient-specific arteries. Especially high stresses in plaque can lead to
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Research, or a related field. Solid research background and practical experience in one or more of the following areas: Reinforcement Learning / Deep Reinforcement Learning Fine-tuning and Application
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, the theoretical foundations and the evaluation of machine learning methods (especially deep learning) Publication in renowned international journals and conferences Supervision of students in seminars and projects
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PhD project, the successful candidate will develop an open-source workflow using deep learning and hierarchical statistical models to streamline the data flow from acoustic recorders to ecological
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biologically-inspired deep learning and AI models (NeuroAI). The computational models we work with include vision deep learning models (including topographical deep neural networks), multimodal vision and
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, with a focus on developing rigorous mathematical foundations for AI interpretability. Research directions include mean field theories of deep learning, data attribution methods, renormalization group
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tasks and zero-shot evaluation in linguistic analysis. Profile • Master’s degree (M2) or PhD in computer science, NLP, machine learning, deep learning, or a related field. • Strong experience in machine
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Department/Location: Department of Biochemistry, Central Cambridge PhD Position - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based