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, computer-aided decision support systems Previous experience with using deep learning models (e.g., convolutional neural networks, autoencoders, transformers) for academic research Documented experience in
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, computer-aided decision support systems Previous experience with using deep learning models (e.g., convolutional neural networks, autoencoders, transformers) for academic research Documented experience in
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participation in conferences and events. Desirable It is desirable that the candidate has a Masters or PhD in electronic engineering, computer science or equivalent Fluent in Python and Python Libraries: Scikit
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out rigorous and impactful research into the computational mechanisms of human learning using deep neural network models, and disseminating the findings within the research group, across the wider
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environment and impact with the QR funding allocated for the Faculty of Arts, Business and Social Sciences (FABSS). The plan is to support 0.6fte post-doctoral research fellowships under this scheme. With a PhD
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to investigate the role of brain network dynamics for adaptive behaviour. Our research programme bridges work across scales (local circuits, global networks) and species (humans, mice) to uncover
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software such as recommendation systems, computer-aided decision support systems Previous experience with using deep learning models (e.g., convolutional neural networks, autoencoders, transformers
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Location: South Kensington, London About the role: Applicants are invited to apply for one Marie Skłodowska-Curie Doctoral Network Researcher position funded by Horizon Europe Marie Currie Doctoral
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Stage Researcher (R1) Positions PhD Positions Country United Kingdom Application Deadline 2 Nov 2025 - 23:59 (Europe/London) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer
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testing and stakeholder engagement. Collaborate closely with the PhD researcher to connect environmental data analysis with computational design innovation. Participate in fieldwork in Norwegian glacier