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in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to adel.bibi@eng.ox.ac.uk For more information about working at
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About the role We are seeking a full-time Post Doctoral Research Assistant to join the Oxford Particles Research Group at the Department of Engineering Science (based at the Osney Thermofluids Institute). The position is fixed term for 36 months and will provide opportunities to work on...
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with experience in: Deep learning Medical imaging computing
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in continual learning settings. The core focus is on leveraging Reinforcement Learning (RL) to make the training and deployment of LLMs more computationally and sample efficient. This approach aims
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computational analyses of epigenomic/transcriptomic data and machine learning. Experience in single-cell omics data is desirable. The post holder will be responsible to develop pipelines for the analysis
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) in machine learning or a closely related field you should possess sufficient specialist knowledge in the discipline to work within established research programmes and have an ability to manage own
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methodology, theory, and applications across the areas of Bayesian experimental design, active learning, probabilistic deep learning, and related topics. The £1.23M project is funded by the UKRI Horizon
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About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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About the Role We are seeking an enthusiastic and motivated postdoctoral researcher to apply advanced data analytics and machine learning techniques to real-world clinical data in the field of viral