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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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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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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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on a new project called TRUSTLINE, which is part of the Learning Introspective Control (LINC) DARPA Program. The project aims to develop machine learning (ML)--based introspection and monitoring
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TRUSTLINE, which is part of the Learning Introspective Control (LINC) DARPA Program. The project aims to develop machine learning (ML)--based introspection and monitoring technologies that enable robotic
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. The post is funded by the EPSRC’s Centre to Centre (C2C) Grant, “Mobile Robotic Inspector: Learning to Explore and Manipulate in the Real World” and is fixed-term of 24 months duration. The project will