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are recruiting three PhD students with distinct research foci: PHD 1: The functional role of neural rhuthms for inter-area brain network communicartion PHD2: The neural code for multi-item representation in
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(UTC) Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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Deadline 30 Nov 2025 - 22:59 (UTC) Type of Contract Permanent Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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working memory contents held within. Second, we will use computational spiking-neuron models to explain the results of the experiments and implement the neural mechanisms responsible. These models will also
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; multiple courses to follow from our Teaching and Learning Centre; a complete educational program for PhD students; multiple courses on topics such as leadership for academic staff; multiple courses on topics
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themselves. 2 - Position description The Faculty of Sciences and Bioengineering Sciences, Department Computer Science, Research Group Federated labs AI and Robotics is looking for a PhD-student with a doctoral
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large-scale neural models of the early visual system. Requirements The successful applicants will have: A solid computational background, an interest in cognitive neuroscience and strong deep learning
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Learning Centre; a complete educational program for PhD students; multiple courses on topics such as leadership for academic staff; multiple courses on topics such as time management, handling stress and an
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academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme
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robotic systems and AI models. You will learn how to programme advanced robotic systems and how to implement aspects of deep learning and neural networks for chemical property prediction. You will be part