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30th April 2026 Languages English English English The Kavli Institute for Systems Neuroscience has a vacancy for a PhD in Systems Neuroscience of Neural and Behavioral Algorithms of Pursuit Apply
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-oriented background - You have a genuine interest in signal processing and machine learning methodology and algorithms - You obtained good grades in courses related to the topics relevant to this PhD
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research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we live in. Your
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We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training costs and energy requirements of state-of-the-art deep learning models significantly, while...
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information sciences. In parallel with basic research, we develop ideas and technologies further into innovations and services. We are experts in systems science; we develop integrated solutions from care
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microscopy is often limited by slow acquisition speeds and large volumes of redundant data, restricting its applicability in real-world scenarios. The goal of this PhD project is to develop a snapshot spatio
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, abandonment, comments, peer interaction) Formalization of algorithms for orchestrating educational AI agents : Train RL and LLM agents and study multi-objective optimization (mastery, well-being stability) Work
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candidate for a fully funded PhD studentship focused on the development of next‑generation bio‑based composite materials. This exciting project is delivered in partnership with SHD Composite Materials Ltd, a
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numerical modeling and validation of brain-inspired algorithms Develop circuit-plausible training and inference algorithms, and analyze their behavior in LTspice and Cadence Spectre Perform algorithm–circuit
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Start date: 1st October 2026 The University of Nottingham is seeking an outstanding and highly motivated candidate for a fully funded PhD studentship focused on the development of next‑generation