606 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in United Kingdom
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About us: Applications are invited for a Postdoctoral Research Associate to work on the Improving Communication with Adults with Learning Disabilities (ICALD) research programme, funded by
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the research conducted by master's and doctoral students. This is part of your personality: We are looking for someone with: Minimum Requirements PhD/Doctorate in bioinformatics, computer science, natural
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and present the results at national and international conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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collaborative research environment. Education, Qualifications and Experience We are looking for outstanding candidates with a PhD in physics, electrical engineering, applied mathematics, computer science, or a
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methods suitable for legged systems in physically-realistic simulated environments and on real robots. You should hold or be close to completion of a PhD/DPhil in robotics, computer science, machine
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. You will write research articles and present the results at national and international conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics
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: PhD or equivalent degree in Robotics, Computer Science, Machine Learning, AI, Control Engineering, or a related field. Excellent programming skills and experience with related tools and software. A
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networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity rules which enable effective learning in large and deep networks and is consistent with