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interactions, and computer simulations to quantify the nature and strength of these interactions. The candidate should have experience with analysis of GPS telemetry data and camera traps and subsequent
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, implementing, and optimising advanced AI algorithms, with deep proficiency in machine learning architectures, scalable model development, and high-performance code. The role holder will have the opportunity
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. Apply statistical modelling, machine learning, and deep learning approaches for biomarker discovery, disease stratification, prognostic modelling, and causal inference. Work closely with clinician
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on projects at the intersection of computational neuroscience and machine learning. This position is part of a multi-investigator grant on the role of memory in intelligence systems. The Postdoctoral Fellow
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Computer Science, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch
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: Probabilistic generative models (VLMs, diffusion, flow models) Reinforcement learning & Markov decision processes Causal inference & counterfactual reasoning Mechanistic & physics-informed modeling Agentic AI
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should have experience in real-time processing or FPGA-based prototyping or embedded sensing architectures, or machine-learning-driven analysis for photon-limited measurements. Exposure to event-driven
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-time simulation will be advantageous. • Knowledge and experience in electrical machines and their control. • Knowledge of software such as PSIM, PLECS and MATLAB/Simulink • Prior knowledge and
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conviction record, military or veteran status, sexual orientation, gender expression and/or identity, an individual’s genetic information, domestic violence victim status, familial status, marital status
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sought to join Dr Gabriela Misca's research team on a study investigating policy and practice relating to Armed Forces families. This is an exciting opportunity to contribute to impactful research, engage