2 of 2 Deep Learning Jobs in the Thames Valley

General Theory for Big Bayes" and Grenoble IDEX. Interested applicants should write to us with: a letter of interest, CV, and should require two recommendation letters. Context Bayesian deep learning brings together two of the most important machine learning paradigms: Bayesian inference 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 accurately estimated. Bayesian statistics offers a theoretically well-grounded framework to reason More ❯

will be expected to: Design and build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Assess latest Agentic AI platforms/frameworks and … adherence to data privacy regulations Connect to your skills and professional experience A bachelor's degree (or equivalent) or higher in AI or equivalent. Experience in data science, machine learning, and AI, with a proven track record of delivering AI-driven solutions in a professional setting, using a variety of tools and techniques. Proficient in programming languages such as More ❯