8 of 8 Bayesian Methods Jobs in the East of England

fundamentals Advanced data skills: statistical modelling, machine learning, time-series forecasting, demand prediction, optimisation, inventory management Experience with dynamic pricing, stochastic processes, or Bayesian inference is a plus Preferred Experience Background in pricing, forecasting or optimisation roles within airlines, hospitality, car rentals, e-commerce, or similar dynamic ...

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 ...

replacement for clinical and statistical expertise, but as a powerful complement to it. We hold ourselves to measurable standards of improvement, and we build methods that can be evaluated, reproduced, and trusted in regulatory settings. You will work across the enterprise to define and deliver on AstraZeneca's most … development questions — leading cross-functional teamsspanning the keyBioPharmaceuticalsdisease areas of cardiovascular, renal, metabolic disease, respiratory,immunologyand cell-therapy.You and the team will develop reusable methods and enterprise-scale approaches that measurably advance the late-stage drug pipeline. This is a high-visibility opportunity to shape how AstraZeneca does ...

replacement for clinical and statistical expertise, but as a powerful complement to it. We hold ourselves to measurable standards of improvement, and we build methods that can be evaluated, reproduced, and trusted in regulatory settings. You will work across the enterprise to define and deliver on AstraZeneca's most … teams spanning the key BioPharmaceuticals disease areas of cardiovascular, renal, metabolic disease, respiratory, immunology and cell-therapy. You and the team will develop reusable methods and enterprise-scale approaches that measurably advance the late-stage drug pipeline. This is a high-visibility opportunity to shape how AstraZeneca does ...

senior specialist role focused on understanding the drivers of demand, outcomes, variation, inequalities and cost across our population. You will apply advanced analytical methods to complex system questions and translate findings into clear intelligence that supports senior decision making. The role will work closely with colleagues across analytics … generation and evaluation rather than routine reporting or dashboard development. Main duties of the job You will lead complex analytical and evaluative projects, applying methods such as regression, forecasting, segmentation, risk stratification, causal inference, impact evaluation, cost-effectiveness analysis and statistical modelling where appropriate. You will be experienced ...

Secondmind Labs is seeking a PhD-level researcher to advance probabilistic modelling, Bayesian optimization, and related fields. You will work in collaborative research teams to develop scalable algorithms addressing real-world problems for customers. You will publish papers, contribute to open-source libraries, and help shape ...

website). Key responsibilities Develop your own research program, with a view to developing new tools and techniques for probabilistic models, Bayesian optimization and related fields. Engage in team collaborations to meet research goals and report your research findings both internally and externally. Contribute to internal product … advantage: A background in decision making (Bayesian optimization, bandits, reinforcement learning, active learning) and/or probabilistic modelling and methods (Gaussian processes, Bayesian neural networks, Variational inference, etc). Experience in numerical programming (Python/NumPy/Tensorflow/PyTorch). Experience ...

multi-modal data ingestion and distribution modelling to production-grade visualisation dashboards. Must-have experience: Probabilistic Time Series Forecasting: Experience using probabilistic time series methods (eg, Bayesian, PyMC, Amazon DeepAR) on small or scarce datasets for distribution prediction. Data Lake & DBaaS Integration: Proven ability to build ...