Industrial PhD Applied Research in Supply Chain Planning (O&G)
Core
Conducting applied research at the intersection of machine learning and mathematical optimisation for refinery and supply chain planning in process industries.
Role type
Industrial PhD Applied Researcher (Supply Chain Planning & Optimisation)
Builds
Next-generation optimisation approaches combining AI and data-driven techniques for industrial deployment and academic publication.
Domain
Oil & Gas / Process Industries / Supply Chain Planning
Deliverable
production ML models | research
Required skills
Mathematical modelling, optimisation (exact methods, metaheuristics), machine learning/AI, advanced programming (Python, MATLAB, Julia), interoperability across industrial systems, data visualisation
Preferred skills
O&G industry experience, refinery operations knowledge, optimisation tools (CPLEX, Gurobi), data engineering, user-centric design
Technologies
Python, MATLAB, Julia, CPLEX, Gurobi
Responsibilities
Develop AI-enhanced optimisation methods, address real-world refinery planning challenges, ensure interoperability across industrial platforms, create decision-support tools
Seniority
PhD Candidate, Researcher
