4 of 4 Bayesian Methods Jobs

natural-world systems: messy, noisy, sparse, nonlinear, and only partially observed. Nice to Have Experience with mechanistic models, hybrid ML, Bayesian methods, causal inference, dynamical systems, or uncertainty quantification. Experience designing benchmarks in novel or poorly defined problem spaces. Experience building models that move from research ...

edge algorithms that combine scientific and applied innovation. Candidates should have a strong academic background in Computer Science, expertise in reinforcement learning or Bayesian optimisation, and proficiency in Python. This is an exciting opportunity to contribute to high-impact AI projects within a dynamic multinational team. #J ...

unclear. You should apply if... You have deep expertise across a range of ML techniques (e.g. Transformer‐based NLP, Deep Learning, Tree‐based methods, Bayesian modelling) and the judgment to select solutions that balance theoretical soundness against engineering practicality. You have a proven track record ...

recognition, including Huawei’s Gold Medals and Best Technology Breakthroughs. This role focuses on advancing the state-of-the-art in reinforcement learning, Bayesian optimisation, AI agents, large language models (LLMs), and/or vision-language models (VLMs). You will work at the intersection of fundamental … eagerness to translate cutting-edge ideas into working prototypes and real-world applications. Key Responsibilities Conduct original research in reinforcement learning or Bayesian optimisation for LLMs, leading to publications in top conferences and journals (e.g., NeurIPS, ICLR, ICML). Design and implement new algorithms and models that ...