Research Scientist - Control & Machine Learning

As a Research Scientist, you’ll

• Help shape our research and development agenda, turning challenges from live plants into well-defined research problems.

• Develop and implement methods for modelling, identification, optimisation and control of complex physical systems.

• Design rigorous experiments, establish strong baselines and understand when and why a method works.

• Work with process engineers to incorporate plant physics, operating knowledge and constraints into models and algorithms.

• Work with machine learning and deployment engineers to evaluate promising methods and bring them into production.

• Follow deployed performance, investigate failures, and use what you learn to guide further research.

• Communicate your findings clearly and contribute to the team’s scientific understanding.

What a great fit looks like

• A PhD in control, machine learning, applied mathematics, engineering, physics or a related field, or equivalent research experience.

• A strong research background in one or more of control theory, data-driven control, system identification, Bayesian optimisation, probabilistic modelling, physics-informed machine learning, imitation learning or model-based reinforcement learning.

• Evidence that you can formulate a research question, develop a method and evaluate it carefully, through publications, open-source work or applied research.

• Strong Python skills and experience implementing machine learning models using tools such as Pandas, NumPy, SciPy, PyTorch.

• An interest in working closely with engineers and taking responsibility for how your methods perform in practice.

• Practical experience deploying machine learning and control algorithms.

• A strong interest in climate mitigation.

You don’t need to know about cement. You do need to get excited about the physics, willing to learn from operators and process engineers, and keen to understand why a plant behaves the way it does.

We don’t expect you to tick every box. If you bring depth in a relevant area and these problems excite you, we’d like to hear from you.