51 to 75 of 105 Bayesian Methods Jobs

teams to inform regulatory strategy and HEOR decisions. The role requires strong statistics background, proficiency in SAS, R and Python, and experience with Bayesian or probabilistic ML methods. You will advance analytical workflows in scalable environments. #J-18808-Ljbffr ...

fintech and Cleo's mission to make money easier and more human Nice to have: causal inference depth (CUPED, Bayesian methods, PSM, uplift modelling) and the judgement to know when it's worth the effort Nice to have: genuine enthusiasm for agentic AI as a force ...

products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Benefits Competitive salary and equity in a fast‐growing start‐up We serve lunch every weekday ...

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 ...

delivery, and ensure actionable insights reach senior stakeholders and C-suite executives. You will build dashboards, apply econometrics and Bayesian methods, and translate complex results into practical recommendations, driving ROI and client success. Hybrid work with a central London base. #J-18808-Ljbffr ...

producing strong quantitative evidence to inform strategy and improve outcomes for people and communities. You will develop predictive models, apply Bayesian methods, and analyse time-series data using Python or R and SQL, translating complex findings for non-technical colleagues in a hybrid, 4-days ...

initiative and are deeply accountable to your internal customers and engineering colleagues. Bonus: experience with implementing solutions for adaptive experimentation ML (contextual bandits, Bayesian optimization or RL-based allocation) Additional Information Bring all of you to work We create the conditions for high performers to thrive, through ...

cloud-native stack (Snowflake). As an experienced technical expert and researcher, you'll lead on individual projects that apply advanced predictive and prescriptive methods (such as causal inference, stochastic simulations, Bayesian hierarchical modelling, machine learning and more) to real-world operational and strategic questions such … tools, considering user needs, data quality and management, user experience and engagement and making best use of statistical modelling and/or machine learning methods and working with other team members to deployment and maintain these Use open-source analytical tools (including R or Python) in an open and ...

governance for innovation deliverables.• Lead and develop statisticians through prioritization, coaching, recruitment input, and succession planning.• Work with Biostatistics and Statistical Programming to ensure methods are feasible, robust, reproducible, and submission-ready.• Represent Biometry in governance, asset reviews, development planning, due diligence, and external scientific discussions.• Build external networks … statistical computing environments, with the ability to guide reproducible modelling and simulation workflows.• Proven ability to influence global cross-functional teams and communicate complex methods, assumptions, uncertainty, limitations, and decisions clearly.Knowledge & Experience (preferred):• Experience with advanced data science methods, including digital twins, virtual/external controls, Bayesian ...

Science agenda. We are particularly interested in AI-accelerated approaches that strengthen mesoscale modelling itself, for example surrogate models, data-centric engineering, and Bayesian techniques for uncertainty quantification and addressing model mis-specification, rather than AI/ML applied without a mesoscale modelling base. Applicants should demonstrate ...

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 ...

duties and responsibilities will include, but won't be limited to building and improving sports prediction modelsTo research recent advances in Bayesian updating to better extract signals from noisy dataTo design and build your own models using your own ideasTo work closely with expert traders and developers ...

Statistics, Mathematics, Physics, or similar. You reason about uncertainty and calibration as first-order concerns. Research mindset. You're curious about new methods and actively look for better ways to do things. You try them out, not just read about them. Judgement. You critically evaluate model output – yours … experiments, or lift studies. Marketing mix or attribution modelling. You have used or contributed to models that quantify channel impact or optimise spend. Bayesian methods. You have used hierarchical models, MCMC, or Bayesian updating in real work. Production ML. You have built and shipped ...

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 … 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 ...

bookmaker) Experience with and/or knowledge of Bayesian models, state space models, filtering and smoothing, computational statistics and approximate inference methods Experience with and/or knowledge of machine and statistical learning, deep neural networks, feature engineering, reinforcement learning, dynamic optimisation and optimal control Experience ...

Join us as a Data Scientist, PBWM In this role, you’ll drive and embed the design and implementation of data science tools and methods, which harness our data to drive market-leading purpose customer solutions Day-to-day, you’ll act as a subject matter expert and articulate … statistics are also required Expertise in developing Gen AI, Agentic AI tools for chat bots in addition to understanding workflows and evaluation methods to measure and monitor performance at scale Managing ML, AI models in production with experience of CI/CD, DevOps, and model monitoring with ...

Join us as a Data Scientist, PBWM In this role, you’ll drive and embed the design and implementation of data science tools and methods, which harness our data to drive market-leading purpose customer solutions Day-to-day, you’ll act as a subject matter expert and articulate … statistics are also required Expertise in developing Gen AI, Agentic AI tools for chat bots in addition to understanding workflows and evaluation methods to measure and monitor performance at scale Managing ML, AI models in production with experience of CI/CD, DevOps, and model monitoring with ...

Role We are looking for a biostatistician with expertise in Bayesian modelling to work on probabilistic modelling of physiological data and medical risk. The role focuses on developing statistical frameworks that combine multiple data sources to estimate the probability of life-threatening deterioration and support triage prioritisation. … engineers, medical advisors, and the product team to design models that operate in real-world environments with noisy and incomplete data. Responsibilities Develop Bayesian statistical models to estimate physiological deterioration risk from multi-sensor data Build probabilistic frameworks integrating vital signs, haemodynamic indicators, motion data, and environmental ...

computer science, or equivalent experience with experience in research Proven experience applying machine learning techniques to solve business problems Proven experience in translating technical methods to non-technical stakeholders Strong programming experience in Python and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/…/keras, langchain). R and C++ optional. Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate models, transformers, Knowledge Graphs, Agents, Graph NNs, Deep Learning, computer vision Ability to write production code and object-oriented ...

Master's) in Statistics, Mathematics, Physics, or similar. You reason about uncertainty and calibration as first-order concerns.Research mindset. You're curious about new methods and actively look for better ways to do things. You try them out, not just read about them.Judgement. You critically evaluate model output – yours … modelling. You have used or contributed to models that quantify channel impact or optimise spend.Bayesian methods. You have used hierarchical models, MCMC, or Bayesian updating in real work.Production ML. You have built and shipped supervised ML models end to end – exploration, training, deployment, monitoring.Python. The stack ...

oversee a small team of quantitative experts delivering advanced trial design, modelling, and predictive analytics. The role drives digital twins, external controls, and Bayesian borrowing, while ensuring regulatory alignment and high-impact use cases. Collaboration with Biometry Leadership is essential. #J-18808-Ljbffr ...

Postdoc and Research Fellow positions in Machine Learning, Centre for AI Fundamentals, Manchester, UK Keywords include automatic experimental design, Bayesian inference, human-in-the-loop learning, machine teaching, privacy-preserving learning, reinforcement learning, inverse reinforcement learning, computational rationality and user modelling, and simulator-based inference. More background ...

engineers, and industry experts to deliver real customer value. The role blends research and production, requiring a strong ML foundation, Bayesian methods, and ability to translate research into practical solutions. Hybrid work in London offered. #J-18808-Ljbffr ...

analyses, develop protocols, and provide senior statistical leadership across multiple engagements with clients. The role requires hands-on expertise in Bayesian methods, ITCs, survival analyses, and programming in R and BUGS/JAGS/Stan. Collaboration across geographies is essential, with mentoring duties and business development ...

International Society for Bayesian Analysis is seeking to fill research positions in machine learning at various levels at the University of Manchester. Candidates will engage in groundbreaking research funded by the Turing AI World-Leading Researcher Fellowship, focusing on probabilistic modelling in diverse areas including human ...