1 to 25 of 28 Bayesian Methods Jobs in England

Job Description Summary In this role, you will understand complex and critical business problems, formulates integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs in neuroscience, discover actionable insights and automate process for reducing effort and time for repeated use. Moreover, you will manage the implementation and adherence … Good understanding of clinical study design principles and basic familiarity working with clinical data in a clinical trial (GxP) setting. Strong knowledge and understanding of (multivariate implementations of) statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modelling, longitudinal modelling, Bayesian methods, variable selection methods (e.g., lasso, elastic net … random forest), design of clinical trials. Familiarity with statistical and analytical methods for high dimensional data (e.g. imaging, digital, genetics or -omics data). Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling. Excellent interpersonal and communication skills (verbal and writing) Ability to develop and deliver clear and concise presentations for 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/… disciplines Strong background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, metrics, and benchmarks, 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, PyTorch Lightning, or similar frameworks Strong More ❯

and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics. Proficiency in designing and programming advanced ML algorithms. Ability to apply state-of-the-art research to real-world problems. Proficiency in operating and evolving advanced ML More ❯

and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics. Proficiency in designing and programming advanced ML algorithms. Ability to apply state-of-the-art research to real-world problems. Proficiency in operating and evolving advanced ML More ❯

and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics. Proficiency in designing and programming advanced ML algorithms. Ability to apply state-of-the-art research to real-world problems. Proficiency in operating and evolving advanced ML More ❯

and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics. Proficiency in designing and programming advanced ML algorithms. Ability to apply state-of-the-art research to real-world problems. Proficiency in operating and evolving advanced ML More ❯

and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics. Proficiency in designing and programming advanced ML algorithms. Ability to apply state-of-the-art research to real-world problems. Proficiency in operating and evolving advanced ML More ❯

solver with a desire to learn Organised and self-motivated Desired Skills Master’s degree in machine learning, mathematics or statistics Understanding of probabilistic model development Experience of Bayesian modelling Good understanding of software design principles and best practices Good knowledge of at least one object-oriented language Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and More ❯

solver with a desire to learn Organised and self-motivated Desired Skills Master’s degree in machine learning, mathematics or statistics Understanding of probabilistic model development Experience of Bayesian modelling Good understanding of software design principles and best practices Good knowledge of at least one object-oriented language Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and More ❯

tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate, and deliver impactful solutions in More ❯

tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate, and deliver impactful solutions in More ❯

and data teams to ensure scalable solutions Requirements Extensive experience in data science, including applied statistics and machine learning Familiarity with supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Experience with cloud platforms (GCP 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 ❯

junior team members, leading research projects, and guiding collaborative efforts is a plus. Knowledge of the following machine learning domains is a plus. Generative models leveraging diffusion or Bayesian Flow Networks. Large-scale distributed machine learning training. Knowledge, experience or interest in the following biological domains is a plus. Drug discovery and protein engineering. Understanding of protein More ❯

skills Track record shipping ML 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 We are a well treated bunch, with awesome benefits! If there's something important to you that's not on this More ❯

experience within predictive modelling, machine learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects models, time series forecasting etc Strong programming ability, preferably in Python SQL and relational databases The company offer some great benefits including a bonus More ❯

experience within predictive modelling, machine learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects models, time series forecasting etc Strong programming ability, preferably in Python SQL and relational databases The company offer some great benefits including a bonus More ❯

simulation. Strong mathematical skills, including linear algebra, probability theory, and statistics. Proficiency in version control systems, particularly Git. Ability to write modular, readable, and maintainable code. Experience with Bayesian inference, object tracking, target tracking, or SLAM (Simultaneous Localization and Mapping) is desirable Excellent research literacy, with the ability to comprehend and apply the latest research papers. Experience More ❯

deals. Strong hands-on skills in Excel and PowerPoint, including financial modeling and executive presentations. Solid understanding of statistical modeling techniques such as Linear Regression, Logistic Regression, and Bayesian methods. Excellent communication skills-both written and verbal-with the ability to clearly present complex concepts to non-technical stakeholders. Leadership presence with the ability to inspire teams More ❯

localisation and emission estimation. Using your strong analytical and problem-solving skills, you will work with complex real-world datasets from field deployments and apply a combination of Bayesian inference, machine learning , and data-driven modelling techniques to deliver robust, interpretable results. We are looking for a hands-on, experienced data scientist who can quickly understand our … Detection of emission events (signal processing, anomaly detection, ML classification) Gas modelling for source localisation and quantification Total site quantification of emissions Research and apply machine learning and AI methods to complement physics-based models, improve detection sensitivity, and automate performance assessment Take a key role in advancing Mirico’s gas-modelling capability , driving innovation in localisation accuracy and … or sensor data Experience in atmospheric dispersion, Gaussian plume , or advection–diffusion modelling Knowledge of probabilistic ML or hybrid modelling (combining physics and data-driven approaches) Familiarity with Bayesian inference, MCMC , or probabilistic programming frameworks (e.g., PyMC, Stan, or TensorFlow Probability) Operating data science/ML workloads at scale using tools such as Argo Workflows, Prefect or More ❯

LeadingpharmaceuticalclientnowrequiresaSeniorDataScientisttodrivemarketingeffectivenessviamarketingmixmodellingandothermodels. Thisrolewilloverseedatacollection,extraction,manipulation,analysisandvalidationensuringdataisreadyformodelling. YouwillworkcloselywiththeDataScienceteamtobuildbasemodelsaccordingtoprojectspecificationsandensuretherobustnessandvalidityofthosemodels. Requirements: Strongexperiencedevelopingandimplementingmarketingmixmodels. ExpertinPythonandpreviousexperiencewithRprogrammingandideallywithMMMmodels. StrongexperiencewithPymcisessential. ExperiencewithRegressionbasedmodelsinanMMMcontext. Strongunderstandingofstatisticalmodelling/MachineLearningtechniques. ExperiencewithprobabilisticprogrammingandBayesianmethods Goodworkingknowledgeofcloud-baseddatascienceframeworks. Thisisa6monthcontractpositionwhichprovidesadailyrateof£688(InsideIR35). Intermsofworkingstructure,thisroleishybridwithonedayperweekintheirLondonofficeandtherestremote. More ❯

Strong coding skills in Python, with deep familiarity across ML and data libraries (pandas, numpy, scipy, scikit-learn, tensorflow, pytorch). A broad understanding of machine learning and statistical methods, including NLP, deep learning, Bayesian inference, time-series forecasting, and recommendation systems. Hands-on experience with cloud platforms such as AWS, GCP, or Azure, and exposure More ❯

Strong coding skills in Python, with deep familiarity across ML and data libraries (pandas, numpy, scipy, scikit-learn, tensorflow, pytorch). A broad understanding of machine learning and statistical methods, including NLP, deep learning, Bayesian inference, time-series forecasting, and recommendation systems. Hands-on experience with cloud platforms such as AWS, GCP, or Azure, and exposure 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 ❯

our services. Aid in business growth by engaging in client meetings, presentations, and proposals, highlighting the advantages and functionality of our technological offerings. Required Skills: Skilled in various modelling methods such as active learning, transfer learning, agent-based modelling, optimization, Bayesian inference, entity extraction/resolution, and spatio-temporal modelling. Proficient in developing models from fundamental More ❯