Operations Management faculty and students are part of the Department of Management. The department welcomes applicants from a wide variety of academic disciplines who are united by a desire to research and provide insight into high-technology industries such as energy, telecommunications, e-commerce, banking, pharmaceuticals and biotechnology. Doctoral students also benefit from training and collaboration with Imperial’s other departments such as Computing, Engineering and Mathematics, which provides a rich research community. With its small intake, the programme provides a supportive environment, preparing students for academic careers in top Business Schools worldwide.
The Operations Management theme studies the design and management of production and business processes across the manufacturing and services sectors, focusing particularly on pricing and revenue management, the interface between operations management and marketing, decision-making under uncertainty, as well as stochastic programming and robust optimisation.
Doctoral thesis in Operations Management
|Esma Koca||Release strategies for related products||Dr Wolfram Wiesemann
Professor Tommaso Valletti
|Shubhechyya Ghosal||Distributionally Robust Capacitated Vehicle Routing Problem||Dr Wolfram Wiesemann|
Doctoral students in the department have the opportunity to teach on our analytics and big data modules on programmes such as MSc Business Analytics and our MBA suite.
Benefits of Imperial College London
In addition to the modules offered within the Business School as part of the MRes programme, we have added elective modules from other faculties within Imperial College London, so that students can benefit from specialised training across the university that is relevant to their research. Students will take the Research Methods modules within the Business School and can then take elective modules in relevant modules which may include:
- Traffic Theory & Queuing Systems
- Fundamentals of Statistical Inference
- Applied Statistics
- Computational Statistics
- Machine Learning
- Advanced Statistical Machine Learning and Pattern Recognition
- Operations Research
- Computing for Optimal Decisions
- Computational Finance
- Retail and Marketing Analytics
- Digital Marketing Analytics
- Logistics and Supply-chain Analytics
- Workforce Analytics