Salary: £60,000 - 85,000 per year Requirements: PhD in Machine Learning, Statistics, Optimisation or a related field (or equivalent research experience) Track record of publications in ML, statistics or optimisation venues Experience or strong interest in probabilistic modelling (e.g. Gaussian Processes, Bayesian methods) Knowledge of decision-making methods (Bayesian optimisation, bandits, RL, active learning) Strong numerical programming skills (Python; NumPy; TensorFlow and/or PyTorch) Collaborative mindset and enthusiasm for research excellence and continuous learning Responsibilities: Conduct original research in areas such as probabilistic models, active learning and Bayesian optimisation Collaborate closely with other researchers and applied teams Blend academic-quality research with practical application Contribute to product development and customer-facing research projects Technologies: AI Machine Learning PyTorch Python TensorFlow numpy More: We are a Cambridge-based AI research company developing data-efficient machine learning solutions for complex engineering and optimisation problems. This is an opportunity to join a highly research-driven ML lab with a strong emphasis on theoretical rigour and real-world impact. We publish regularly at top-tier machine learning conferences and contribute to open-source ML libraries. Our hybrid working model allows for flexibility in this dynamic field. last updated 8 week of 2026