6 of 6 Permanent Bayesian Methods Jobs in Cambridge

Postdoc in Bayesian machine learning, AstraZeneca, Cambridge, UK Mar 29, 2018 PREDICTING DRUG TOXICITY WITH BAYESIAN MACHINE LEARNING MODELS We’re currently looking for talented scientists to join our innovative academic-style Postdoc. From our centre in Cambridge … uncertainty in the inputs and propagate this uncertainty into the predictions. In addition, you will promote the use of Bayesian methods across safety pharmacology and biology more generally. You are also expected to present your findings at key conferences and in leading publications This project ...

reasoning with practical software engineering to calibrate models against measurements, test predictions on independent cases and build uncertainty analysis into the simulation workflow. Your methods and software will help engineers and investors understand what the simulator predicts and the limits of those predictions. We welcome people from AI systems … and other fields where simulation is tested against experiments. You might bring systems engineering experience and an interest in developing uncertainty methods, or experience in mathematical modelling and scientific computing that you want to apply to AI infrastructure. What you will do Develop and implement methods to calibrate ...

sitting at the intersection of modern machine learning and quantum computing — with two complementary directions. ML for quantum — using neural networks and learning-based methods to accelerate quantum computation (e.g. circuit optimisation and compilation, error mitigation, calibration, variational-parameter optimisation, and surrogate modelling of quantum processes). …/with quantum — building and adapting classical AI methods, including neural networks and large language models, so they can benefit from quantum hardware and algorithms. You don't need to be a world expert in either quantum or LLMs — but you should be genuinely comfortable with neural networks and ...

used to understand next-generation energy and thermal management systems. We use techniques like reinforcement learning, multi-objective optimization, and Bayesian methods to model the processes involved in bringing new energy technologies to market, manage uncertainty, and optimize decisions. Responsibilities: Bring your computer science/software … other interns, and stakeholders. You will learn: How to scope and manage your own time and project(s) Computer science, machine learning, and AI methods beyond your current course. Qualifications : Studying Bachelors in Computer Science, AI, Physics or a related discipline Software development skills in at least ...

and a training loop, and who has built systems from scratch because they wanted to understand how they work. Key Responsibilities: Build RL, Bayesian and LLM-agent-driven design-space exploration over gem5 and cycle-accurate models, using fast simulation for broad search and detailed models ...

problems and judge what is worth attempting. Desirable Experience applying machine learning to engineering optimization or design exploration, such as surrogate modelling or Bayesian optimization. Familiarity with engine simulation and CAE tools such as GT‐SUITE or Simcenter. Bachelor's degree in engineering or a related technical ...