Control Systems Code Validation

My preferred candidate would be a control-engineering researcher or experienced industrial research engineer, ideally with a PhD in control systems, electrical engineering, mechanical engineering, systems engineering or a closely related subject. Equivalent practical experience is acceptable; a PhD alone is not enough.
Skill What I would require
Control systems and optimisation Practical experience implementing and evaluating model predictive control, including constraints, changing workloads and switching costs.
Python and reproducible simulation Ability to inspect numerical code, install a documented environment, rerun experiments and preserve configurations, logs and results.
Experimental design and statistics Ability to assess fair comparisons, held-out testing, uncertainty, correlated observations, repeated seeds and whether service performance has genuinely been preserved.
Learning-based control Enough experience with reinforcement learning and learned predictive models to recognise weak or unfair comparisons.
Energy or thermal systems Preferably experience with data-centre optimisation, computing-resource management, cooling, building control or another coupled energy system. Direct data-centre experience is desirable rather than mandatory.