1 to 25 of 31 Permanent Bayesian Methods Jobs in the UK excluding London

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 ...

deployment in laboratories, hospitals, and public health organisations worldwide. Your Role: As a (Senior) Scientist, you will design, develop, and evaluate novel computational methods for translating metagenomic sequencing data into actionable results in a clinical or public health context. You will develop algorithms and AI/ML methods … Develop ML/AI techniques to address real-world problems in the pathogen genomics space, in collaboration with scientists across EIT Validate and benchmark methods using public and internal datasetsWork with bioinformaticians and software engineers to implement methods in scalable, reproducible, and modular workflows Communicate technical work clearly ...

communication skills. Beneficial to have: Experience in a similar role in a professional football environment. Experience with Time-Series Analysis & Forecasting. Experience with Bayesian inference/MCMC. What's in it for you? We are committed to ensuring everyone can flourish in their roles. To achieve this ...

and machine learning. Statistics & Math: Deep understanding of statistical inference, regression analysis, probability theory, decision trees, and hypothesis testing (p-values, confidence intervals, Bayesian testing etc.). Data Visualization: Hands‐on experience building interactive dashboards using tools like Power BI, Looker, or Python libraries. Experience: 3+ years ...

experimental data, and in your penultimate year of study. Experience working with datasets using Python, R, SAS, MATLAB, or other statistical software. Experience with methods of statistical data analysis (e.g., linear models, hypothesis testing, multi-level models, Bayesian methods, etc.). Preferred qualifications: Experience with … search techniques. Produce quantitative and qualitative modeling of business dynamics, user behavior, and more. Identify areas for further investigation as well as creating innovative methods of analysis. Please complete your application before 23rd October 2026. We encourage you to apply as early as possible as we review applications ...

pricing models. Turning pricing opportunities into measurable hypotheses, experiments and production changes. Evaluating pricing performance through backtesting, online testing and commercial metrics. Developing Bayesian, multi-armed bandit and other optimisation approaches for dynamic pricing. Working with commercial, finance and product teams to understand pricing performance and recommend … code, testing and code review, alongside strong SQL. A solid grounding in machine learning techniques such as gradient boosting, GLMs, Bayesian methods and multi-armed bandits, or comparable experimentation and optimisation methods. Experience designing, running and evaluating pricing experiments using both commercial and statistical measures. ...

technical leadership: mentoring, setting standards, and influencing scientific and technical direction beyond your own projects. Beneficial Skills Practical experience with active learning, Bayesian optimisation, conformal prediction, or uncertainty quantification in iterative real‐world loops. Familiarity with retrosynthesis ML, computer‐aided synthesis planning (CASP), or reaction‐condition/ ...

what questions should be explored next. Key Responsibilities & Skills ** Develop predictive models and forecasts to identify potential future outcomes and emerging trends ** Applying Bayesian modelling, uncertainty estimation and statistical validation ** Carry out segmentation and subgroup analysis to identify meaningful differences and patterns ** Analyse longitudinal and time-series ...

required to obtain UK Security Clearance. Desirable Experience Experience with any of the following would be beneficial: Statistical modelling, Bayesian methods, uncertainty estimation, or probabilistic techniques. Synthetic data generation, multi-modal AI, or action recognition. Machine learning development tools, experiment tracking, dataset management, or CI/ ...

investigate complex datasets and answer challenging research questions. This could include building models to understand and predict outcomes, applying Bayesian methods, testing statistical assumptions, identifying patterns and analysing how results change over time . You'll often be working with data from multiple sources, so experience … determining the appropriate data and analytical approach, and communicating findings clearly to non-technical stakeholders. Key skills: ** Strong quantitative and statistical analysis experience ** Bayesian modelling and statistical validation ** Python or R ** Predictive modelling, forecasting and segmentation ** Experience working with large, complex datasets ** Ability to work with incomplete ...

rich environments Strong statistical knowledge Experience with product analytics and behavioural tracking Experience mentoring or coaching other analysts Nice to have Knowledge of Bayesian or Frequentist experimentation approaches Experience with event-level analytics platforms Predictive analytics exposure The team You'll report into the Analytics Team Lead ...

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 ...

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 ...

research with mentoring PhD students and collaboration with clinicians, computer scientists and mathematicians. Proficiency in Python, Julia, R and MATLAB, plus experience with Bayesian inference and HPC #J-18808-Ljbffr ...

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 ...

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 ...

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 ...

Fundamentals, Manchester, UK. These lectureships form part of a strategic investment in fundamental AI research; candidates should have strong backgrounds in Bayesian inference, automatic experimental design, human-in-the-loop learning, machine teaching, privacy-preserving learning, reinforcement learning, and related areas. #J-18808-Ljbffr ...

quality, customer effort, process adherence, consistency, fairness, durability of resolution and cost effectiveness. Identify the root causes of issues by combining machine learning, statistical methods and domain expertise from colleagues to understand what genuinely drives customer outcomes. Identify and test solutions Turn analytical insight into concrete proposals to improve … Python skills, with experience working with large, complex and imperfect datasets. Strong grounding in statistical analysis (e.g., classical ANOVA, non-parametric uncertainty quantification, Bayesian estimation) and causal inference, with experience designing both controlled experiments and observational studies. Experience applying machine learning, statistical modelling, NLP and LLM-based ...

team working at the intersection of artificial intelligence and quantum sensing. The positions will focus on the development and deployment of real-time AI methods for the autonomous optimisation of spin-based quantum sensors associated to solid-state defects. The successful candidates will join a research environment that … and conferences, and/or other appropriate media. Other duties Understand the intellectual property landscape relevant to the project and seek to protect the methods and techniques developed during the course of the project. Develop research objectives and proposals for own or joint research with the assistance ...

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 ...

Develop an independent research program focused on new tools and techniques for probabilistic models, Bayesian optimization, and related fields Collaborate with research teams to meet research goals Report research findings internally and externally Contribute to internal product development and customer research projects Apply cutting-edge machine learning … journals Background in decision making, including Bayesian optimization, bandits, reinforcement learning, or active learning (advantage) Background in probabilistic modelling and methods, including Gaussian processes, Bayesian neural networks, or variational inference (advantage) Experience in numerical programming with Python, NumPy, TensorFlow, or PyTorch (advantage) Experience ...

hormonal rhythms observed across individuals. To characterise this variability, you will take advantage of unique in its kind datasets and advanced mathematical and computational methods and help develop personalised models. The practical element of your project will be based on, but not limited to, time series analysis, network analysis … being welcoming and supportive. The applicant should have high proficiency with scientific computer programming in Python, Julia, R and/or MATLAB, parameter estimation methods and HPC simulations. Experience with dynamical systems theory and mathematical modelling using ODEs and/or DDEs is desirable. The vacancy ...

team working at the intersection of artificial intelligence and quantum sensing. The positions will focus on the development and deployment of real-time AI methods for the autonomous optimisation of spin qubits associated to solid-state defects. We expect the candidate to supervise on-going work on an existing … and conferences, and/or other appropriate media. Other duties Understand the intellectual property landscape relevant to the project and seek to protect the methods and techniques developed during the course of the project. Develop research objectives and proposals for own or joint research with the assistance ...

delivery teams within the UK Defence or Aerospace sectors. Experience in the practical application of mathematical techniques such as Monte Carlo simulation or Bayesian inference. Experience working with MoD assessment frameworks and an understanding of the UK Defence Science and Technology (S&T) landscape. Experience conducting peer … production environment. Experience working within secure environments and an understanding of the constraints of working with classified information. Expert knowledge of numerical methods, optimisation, and statistical analysis within a defence context Proficiency in mathematical programming using Python (NumPy, SciPy), FORTRAN, or Julia. Familiarity with simulation tools and synthetic environments ...