1 to 25 of 29 Remote/Hybrid Applied Mathematics Jobs in the UK

depth, judgment, and evidence of exceptional work than credentials. You may have PhD‐level training in machine learning, physics, biology, chemistry, applied mathematics, computational biology, or another systems‐oriented discipline. You should have strong foundations in one or more of: applied mathematics, statistics, optimisation … probabilistic modelling, causal inference, dynamical systems, scientific ML, or related areas. You may also be an exceptional applied ML engineer without a PhD, with a track record of building models for complex real‐world systems. Experience with biological data is useful, but not required. What matters most ...

/CD workflows Exposure to MLflow or similar model tracking/deployment tools Strong foundation in statistics, probability, linear algebra, and applied mathematics Experience delivering models such as: Churn prediction models Customer segmentation frameworks Next Best Action/propensity models Time series forecasting models About … equivalent experience in a highly quantitative discipline (e.g. Mathematics, Statistics, Physics, Computer Science, Data Science) Strong project capability with a hands-on technical mindset Comfortable working in fast-moving, agile environments Able to communicate insights clearly to both technical and non-technical stakeholders Collaborative, proactive, and delivery-focused Additional ...

seeking candidates who demonstrate the following skills and experience:* Bachelor’s or Master’s degree in Engineering, Operations Research, Computer Science, Applied Mathematics, or a related field.* Hands-on experience with simulation modelling techniques (discrete event simulation, agent-based simulation, system dynamics) and translating operational systems into … libraries.Demonstrated proficiency in at least one of the following:* + Modelling, Simulation & Digital Twins + Optimisation + Machine Learning, Data Science and applied AI techniques* Solid grasp of statistical analysis, experimental design, and data visualisation.* Experience applying AI or advanced analytics in operational or asset‐intensive environments.* Ability ...

technical expert pushing the boundaries of what AI can do for drug discovery. Your deep knowledge of machine learning, strong coding foundations, and applied experience in model development will play a key role in advancing our Drug Discovery Platform. You will act as a technical mentor, contribute … Have Qualifications: Strong problem-solving skills, autonomy and a collaborative mindset. PhD or equivalent practical experience in Machine Learning, Computer Science, Applied Mathematics or a related field, with at least 8 years of experience. Strong programming skills in Python and proficiency with Deep Learning frameworks (e.g., PyTorch ...

technical expert pushing the boundaries of what AI can do for drug discovery. Your deep knowledge of machine learning, strong coding foundations, and applied experience in model development will play a key role in advancing our Drug Discovery Platform. You will act as a technical mentor, contribute … Have Qualifications: Strong problem-solving skills, autonomy and a collaborative mindset. PhD or equivalent practical experience in Machine Learning, Computer Science, Applied Mathematics or a related field, with at least 8 years of experience. Strong programming skills in Python and proficiency with Deep Learning frameworks (e.g., PyTorch ...

technical expert pushing the boundaries of what AI can do for drug discovery. Your deep knowledge of machine learning, strong coding foundations, and applied experience in model development will play a key role in advancing our Drug Discovery Platform. You will act as a technical mentor, contribute … Have Qualifications: Strong problem-solving skills, autonomy and a collaborative mindset. PhD or equivalent practical experience in Machine Learning, Computer Science, Applied Mathematics or a related field, with at least 8 years of experience. Strong programming skills in Python and proficiency with Deep Learning frameworks (e.g., PyTorch ...

technical expert pushing the boundaries of what AI can do for drug discovery. Your deep knowledge of machine learning, strong coding foundations, and applied experience in model development will play a key role in advancing our Drug Discovery Platform. You will act as a technical mentor, contribute … Have Qualifications: Strong problem-solving skills, autonomy and a collaborative mindset. PhD or equivalent practical experience in Machine Learning, Computer Science, Applied Mathematics or a related field, with at least 8 years of experience. Strong programming skills in Python and proficiency with Deep Learning frameworks (e.g., PyTorch ...

technical expert pushing the boundaries of what AI can do for drug discovery. Your deep knowledge of machine learning, strong coding foundations, and applied experience in model development will play a key role in advancing our Drug Discovery Platform. You will act as a technical mentor, contribute … Have Qualifications: Strong problem-solving skills, autonomy and a collaborative mindset. PhD or equivalent practical experience in Machine Learning, Computer Science, Applied Mathematics or a related field, with at least 8 years of experience. Strong programming skills in Python and proficiency with Deep Learning frameworks (e.g., PyTorch ...

large and complex datasets, and collaborating closely with data engineers and data scientists to deliver robust analytical products. Advanced knowledge of applied mathematics, statistics, and numerical analysis, with experience using techniques such as optimisation, time series analysis, simulation or predictive modelling to generate insight and support decision ...

large and complex datasets, and collaborating closely with data engineers and data scientists to deliver robust analytical products. Advanced knowledge of applied mathematics, statistics, and numerical analysis, with experience using techniques such as optimisation, time series analysis, simulation or predictive modelling to generate insight and support decision ...

collaborating closely with data engineers and data scientists to deliver robust analytical products. Skills/Knowledge Essential Advanced knowledge of applied mathematics, statistics, and numerical analysis, with experience using techniques such as optimisation, time series analysis, simulation or predictive modelling to generate insight and support decision making. ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...

commercial, product, and engineering stakeholders so they are understood and acted on. Bonus points: Experience with reinforcement learning or causal inference in applied … commercial settings. Familiarity with energy markets, power trading, or portfolio management. PhD or equivalent research depth in a quantitative discipline (statistics, applied mathematics, physics, operations research, or similar). Ability to reason about the trade-offs between optimisation solvers (Gurobi etc) and gradient-based ML methods (PyTorch ...