6 of 6 Permanent Bayesian Methods Jobs in Oxfordshire

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 ❯

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 ❯

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 ❯

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 ❯

Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that's reinventing how the world designs and … all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science, and engineering to push the boundaries of what's More ❯