26 to 50 of 66 Permanent Bayesian Methods Jobs

managers and various business stakeholders to ensure top-quality outcomes to meet internal objectives. Investigate and adopt innovative concepts that offer tangible benefits. Employ techniques like Deep Learning, Bayesian Modelling, Large Language Models, Product embedding, Recommendation Systems, and Computer Vision. To be successful in the role, you'll need: 5+ years of hands-on data science experience. More ❯

have: Background in Machine Learning, Statistics, Applied Mathematics, Computer Science or a related field (MSc or PhD ideal, but open to strong BSc candidates) Hands-on experience with Bayesian optimization, ideally in noisy or low-data regimes Familiarity with probabilistic modelling and the underlying mathematical/statistical principles. Demonstrable experience with machine learning frameworks such as JAX … team setting, bringing new ideas to life. Your role As a Data Scientist, you’ll work at the intersection of materials science and AI, designing and implementing data-driven methods to optimise formulations and performance of sustainable materials. You'll own the data science function, collaborating closely with our R&D and product teams to accelerate experimentation and discovery. More ❯

non-technical audiences What we are looking for: A degree (2:1 or above) in Computer Science, Data Science, AI or similar Solid grounding in statistics – understanding of Bayesian and frequentist approaches, distributions, etc. Knowledge of core ML techniques like linear/logistic regression, random forests, time series models, etc. Familiarity with SQL and Python Bonus points More ❯

mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new algorithms when an More ❯

management Key Experience: Strong academic background with a minimum 2:1 Degree in Computer Science (or similar) Strong numerical background with a knowledge of key statistical principles – eg Bayesian and frequentist statistics Experience with multiple programming languages including SQL and Python Familiarity with large language models Understanding of ML algorithms This is an excellent opportunity for a More ❯

in the AI Lab. Responsibilities Develop new ML models and AI techniques Lead on research projects within a global team Review relevant AI/ML literature to identify emerging methods, technologies, and best practices Explore new data sources and discover techniques for best leveraging data Minimum Qualifications A Master's or PhD in a field related to AI/… Architecture or related disciplines Strong background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, and deploying production-ready solutions) Familiarity in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with PyTorch, TensorFlow, JAX or similar frameworks Strong More ❯

technical audiences. A self-starter who thrives in a fast-paced R&D environment. Experience in catastrophe modelling, especially around exposure and vulnerability. Applied statistical skills such as Bayesian statistics, uncertainty quantification, or Extreme Value Theory. Knowledge of machine learning applications in climate risk. Familiarity with cloud platforms (e.g., AWS, Google Cloud). If this role looks More ❯

technical audiences. A self-starter who thrives in a fast-paced R&D environment. Experience in catastrophe modelling, especially around exposure and vulnerability. Applied statistical skills such as Bayesian statistics, uncertainty quantification, or Extreme Value Theory. Knowledge of machine learning applications in climate risk. Familiarity with cloud platforms (e.g., AWS, Google Cloud). If this role looks More ❯

doing causal inference/segmentation Ability to explain ideas and present results to non-technical audiences Strong stakeholder management skills Experience with marketing mix models and/or Bayesian time series would be a big plus Strong theoretical understanding and experience with key classification and regression models is a plus Please note this role is offered on … doing causal inference/segmentation Ability to explain ideas and present results to non-technical audiences Strong stakeholder management skills Experience with marketing mix models and/or Bayesian time series would be a big plus Strong theoretical understanding and experience with key classification and regression models is a plus Please note this role is offered on More ❯

maintenance. The ideal candidate will be a good communicator and have a growth mindset with an enthusiasm for scientific discovery and strong interest in applying a combination of AI methods and mathematical models toward understanding mechanistic aspects of cellular processes with all experimental labs at Altos Labs. The ideal candidate is particularly interested in multi-scale (systems) biochemistry and … loop between experimental and theoretical work, at multiple scales, from molecules to cells, tissues and even whole organisms. Working at the interface between mathematical and computational models, and AI methods, with the aim of establishing design principles of rejuvenated cells. Collaborating with both experimental and computational scientists across Altos. Influence best practices in areas such as Bayesian … Biology, Computational Biology, Computer Science, or closely related field with strong emphasis in biological modeling. Relevant industry and/or academic experience. Expertise and a track record of using methods from artificial intelligence for biological design. Record of applications of dynamical systems to problems of synthetic biology. Record of applications of data driven modeling methods and AI to More ❯

An excellent academic record, including a undergraduate degree in a STEM subject with a strong data science component or equivalent. Strong mathematical ability - particularly in linear algebra and Bayesian statistics A minimum of four days a week in our Holborn office, preferably Monday to Thursday Ability to manage time effectively and tight deadlines; flexibility to adapt to More ❯

Understands complex and critical business problems from a variety of stakeholders and business functions, formulate integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. To manage the definition, implementation and adherence to the overall … biostatistics, or other quantitative field (or equivalent). More than 6 years experience in clinical drug development with extensive exposure to clinical trials. Strong knowledge and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods (e.g., lasso, elastic net More ❯

existing results in the broad field of machine learning. You will be apart of a highly unique research group across Natural Language Processing, Large Learning Models, deep learning, Bayesian & Signal Optimization with the exciting transition to the world of financial predication through the prism of machine learning. The most exceptional team members combine strong technical skills and More ❯

existing results in the broad field of machine learning. You will be apart of a highly unique research group across Natural Language Processing, Large Learning Models, deep learning, Bayesian & Signal Optimization with the exciting transition to the world of financial predication through the prism of machine learning. The most exceptional team members combine strong technical skills and More ❯

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, UK you'll be in a global pharmaceutical environment, contributing to live projects right from the … advisor, who'll provide you with the guidance and knowledge you need to develop your career. You will be part of the Quantitative Biology group and develop comprehensive Bayesian machine learning models for predicting drug toxicity in liver, heart, and other organs. This includes predicting the mechanism as well as the probability of toxicity by incorporating scientific … will be used to account for 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 is in collaboration with Prof. More ❯

libraries like mplsoccer . Advanced MLOps & Modelling: Deeper experience with the Vertex AI lifecycle (especially Pipelines ) and advanced modelling techniques relevant to football (player valuation, tactical analysis). Bayesian Modelling: Experience with probabilistic programming (e.g., PyMC). Stakeholder Management: Proven success working directly with business stakeholders to define and deliver impactful solutions. What They Offer Work that More ❯

libraries like mplsoccer . Advanced MLOps & Modelling: Deeper experience with the Vertex AI lifecycle (especially Pipelines ) and advanced modelling techniques relevant to football (player valuation, tactical analysis). Bayesian Modelling: Experience with probabilistic programming (e.g., PyMC). Stakeholder Management: Proven success working directly with business stakeholders to define and deliver impactful solutions. What They Offer Work that More ❯

libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualisation. Familiarity with Monte Carlo simulations in Python and/or PyMC3 for Bayesian modelling is a plus. Familiarity with statistical confidence testing. Understanding and expertise in statistical modelling techniques is a plus. Strong communication, stakeholder management, and people management skills. Ability More ❯

libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualisation. Familiarity with Monte Carlo simulations in Python and/or PyMC3 for Bayesian modelling is a plus. Familiarity with statistical confidence testing. Understanding and expertise in statistical modelling techniques is a plus. Strong communication, stakeholder management, and people management skills. Ability More ❯

Science, Engineering, Statistics, Economics, Mathematics, or a related technical or quantitative field, or equivalent practical experience. Nice to have: Experience with advanced experimentation methodologies (e.g., Bayesian methods, multi-armed bandits, causal inference). Experience specifically building or managing platforms for internal developers/users. Proven track record of successfully scaling experimentation programs and culture within an More ❯

evolve an internal experimentation platform used company-wide Own and scale the stats engines and inference tools that power experiment analysis Build and apply advanced statistical models – especially Bayesian and casual inference approaches Help design new features that make large-scale experimentation easy Act as a go-to mentor for casual inference and experimentation, mentoring others Collaborate … cross-functional teams to keep improving experiments They’re looking for: 5+ years' experience in data science, with at least 3 years at senior level Strong expertise in Bayesian statistics, causal inference, and experimental design Advanced Python programming skills and fluency in SQL Hands-on experience building or contributing to experimentation platforms or data infrastructure Familiarity with More ❯

evolve an internal experimentation platform used company-wide Own and scale the stats engines and inference tools that power experiment analysis Build and apply advanced statistical models – especially Bayesian and casual inference approaches Help design new features that make large-scale experimentation easy Act as a go-to mentor for casual inference and experimentation, mentoring others Collaborate … cross-functional teams to keep improving experiments They’re looking for: 5+ years' experience in data science, with at least 3 years at senior level Strong expertise in Bayesian statistics, causal inference, and experimental design Advanced Python programming skills and fluency in SQL Hands-on experience building or contributing to experimentation platforms or data infrastructure Familiarity with More ❯

data structures using SQL or Python for data analysis. Statistical mindset with the ability to setup, run and analyse RCTs and split tests. Extra bonus for knowledge of Bayesian Statistics. Passionate about helping small businesses thrive-belief in our mission is important! The salary We expect to pay £55,000 - £70,000 for this role. However, we More ❯

data structures using SQL or Python for data analysis. Statistical mindset with the ability to setup, run and analyse RCTs and split tests. Extra bonus for knowledge of Bayesian Statistics. Experience optimising user journeys and driving customer engagement. Passionate about helping small businesses thrive-belief in our mission is important! The salary We expect to pay More ❯

Theo Damoulas and Prof. Mark Steel, as part of the Turing-Lloyds Register Foundation funded project 'Air Quality Sensor Networks'. This project is likely to involve hierarchical Bayesian models, nonparametric Bayesian inference, graphical models, active learning, experimental design and issues in spatio-temporal inference such as non-stationarity and non-separability. The expectation … or Computer Science or Applied Mathematics (or you will shortly be obtaining it). You should have a strong background in one or more of the following areas: Bayesian inference, spatial statistics, probabilistic machine learning. The post is based in the Departments of Statistics and Computer Science (joint appointment) at the University of Warwick, but the work More ❯