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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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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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, 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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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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, 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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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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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
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duration of the PhD research. Please see the RePIM project website (https://repimnetwork.eu/recruitment ) for further information. Qualification requirements PhD stipends are allocated to individuals who
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applications for one or more fixed-term, non-tenure-track full/part-time Instructor positions to teach on a term by term basis for the 2025-2026 academic year. Some of these appointments may be reviewed
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research profile, and an international network around big data in marine sciences. The candidate will have access to NIOZ’s high-performance computing cluster, GPU nodes for deep learning, dedicated data