Short Description

Are you fascinated by data-driven approach in inventory management? Are you curious about how human inventory decision makers interact with the solutions obtained from data-driven approach?

Job Description

The School of Industrial Engineering is one of the longest-established IE Schools in Europe, with a strong presence in the international research and education community, especially in the field of Operations Management and Operations Research. OM and OR are at the core of the undergraduate IE program. The graduate programs (MSc and PhD) in Operations Management & Logistics attract top-level students from all over the world. Researchers in the school are member of the Beta research school and participate in industrial activities with members of the European Supply Chain Forum.

The group Operations, Planning, Accounting and Control (OPAC) conducts research in the area of Operations Management, with specific emphasis on

• Planning and Control in Manufacturing, Services, and Supply Chains;
• Distribution Logistics;
• Maintenance and Reliability;
• Finance and Accounting, oriented towards operational processes.

The Eindhoven AI Systems Institute (EAISI) combines all TU/e Artificial Intelligence activities. Top researchers from various research groups work together to create new and exciting AI methodologies and applications with a direct impact on the real world. TU/e has been active in the field of AI for many years, which gives the new institute an excellent starting position to build upon.

Applicants should have completed (or be close to completion of) a Master's degree in mathematics, operations management, operations research, econometrics, industrial engineering, or a closely related discipline, with a solid background in mathematical methods. Fluency in English is required.

The project

Demand uncertainty is one of the main challenges in supply chains. Optimizing inventory to maximize profit without knowing the demand, has never been an easy task for the decision makers in practice. When the demand is highly uncertain without knowing the distribution, the inventory decisions will be even more complex.

To tackle this problem, we will conduct a comprehensive study of the data-driven robust optimization (DDRO) approach, theoretically, empirically, and behaviourally. In theory, we will develop a new DDRO approach. In collaboration with companies, we will analyse the empirical data carrying out the new approach. In the behavioural perspective, we will validate and evaluate the DDRO solution and other AI solutions (e.g. obtained from reinforcement learning) to support human decision makers.

We expect you to:

• develop the project proposal based on academic literature;
• build mathematical models in the DDRP approach, and compare DDRO approach and reinforcement learning approach;
• Apply new approach in empirical data
• Design lab/online experiments;
• Analyse behavioural data obtained from experiment;
• communicate the practical implications of this research to specific stakeholders and the general public;
• and present the findings at conferences and publish papers in internationally renowned journals.

• A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
• A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
• To develop your teaching skills, you will spend 10% of your employment on teaching tasks.
• To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program).
• A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
• Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
• Should you come from abroad and comply with certain conditions, you can make use of the so-called '30% facility', which permits you not to pay tax on 30% of your salary.
• A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
• Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.