26 to 33 of 33 Neural Network Jobs in the UK excluding London

our rapidly expanding Data and Decision Support Capability. The Data and Decision Support Capability has teams working in: reinforcement learning; NLP/LLMs; knowledge graphs and graph based neural networks; AI for RF and EW, radar, sonar, acoustics, AI for image and video recognition tasks. The latter includes both computer vision and remote sensing application areas. You should … of the following domains: AI/ML for imagery including applied to remote sensing applications. Reinforcement learning. Natural Language Processing. Large Language Models. Knowledge graphs and graph-based neural nets. AI/ML for RF and EW, radar, sonar, acoustics. Autonomy Desirable Knowledge, Skills and Experience: Evidence of publication in relevant journals and conferences is highly advantageous. Why More ❯

Models" (UCL , Oxford, Imperial, Edinburgh, Cardiff, Manchester and Surrey) and with its industrial partners. Key responsibilities include working on deep learning, probabilistic modelling, deep generative modelling, and graph neural networks. Additional responsibilities include developing research objectives and proposals; presentations and publications; assisting with teaching; liaising and networking with colleagues and students; planning and organising research resources and workshops. … a strong publication record. Excellent mathematical and programming skills are essential, with experience in two or more of Bayesian methods, deep learning, deep generative models, reinforcement learning, graph neural networks. Interviews are expected to happen in July 2025. Applicants are encouraged to guarantee that referees can submit their letters before such date. The interviews will be done via More ❯

and deep learning. On the one hand, Bayesian learning provides a theoretically sound framework to formalise the estimation of the architecture and the parameters of deep neural network models. On the other hand, deep learning offers new tools in Bayesian modelling, e.g. to learn flexible nonparametric priors or computationally efficient posterior distribution approximations. State of the art … The field of machine learning has recently been much impacted by deep learning. Deep neural networks are now at the basis of the state-of-the-art in computer vision, natural language processing, to cite just a few. While very effective, these models are computationally costly and require large quantities of data for their many parameters to be … grounded framework to reason about uncertainty, and it is one of the cornerstones of modern machine learning. At the same time, the theory at the basis of deep neural networks is not yet very well understood and its grounds must be laid out. Although the interaction between these two learning paradigms is relatively under-explored, there is a More ❯

the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for spoken language applications - Develop and/or apply statistical modelling methods (e.g. deep neural networks), optimizations, and other ML techniques to different applications in spoken language engineering Company: Amazon Qualifications: BASIC QUALIFICATIONS - PhD, or a Master's degree and experience in CS, CE More ❯

projects through to delivery. Ideally, experience applying AI in a commercial or customer-focused environment. Hands-on knowledge in areas such as signal processing, reinforcement learning, neural network training, or multi-agent systems. Familiarity with research publishing processes and participation in academic or industry conferences. Responsibilities Leading research initiatives that explore the practical application of AI within More ❯

history with good grades throughout Skilled in building computer vision solutions, with a focus on object detection and motion tracking. Knowledgeable in modern machine learning techniques, including convolutional neural networks (CNNs) and transformer models. Experience with tracking methods, including the use of Kalman filters. Aware of traditional, lower-resource image processing techniques such as blob detection. Proficient in More ❯

customer knowledge to ensure proposals meet their needs. We are looking for: We are particularly interested in candidates with experience in ONE of the following: Neuromorphic Computing, Spiking Neural Networks and event-based event monitoring/sparse data. Advanced statistics and experience operationalising academic research. Security clearance: You must be able to gain and maintain the relevant UK More ❯

candidates with a range of experience levels. Responsibilities: Joining our growing and versatile team, you'll contribute to the development and verification of groundbreaking ML and Neural Network hardware. Collaborating with experts across global design centers, you'll drive impactful projects and help deliver Arm's next-generation IP using the most sophisticated tools and methodologies. As …/C++ models of a microarchitecture. Familiarity with Arm architecture and AMBA bus protocols. Experience with CI platforms and version control tools. Practical knowledge of machine learning and neural networks. In Return: With offices around the world, Arm is a diverse organisation of dedicated, innovative and highly proficient engineers. As well as a friendly and high-performance working More ❯