Are you passionate about Artificial Intelligence (AI) and/or Operations Research (OR)? Would you want to do research inside a leading AI Institute? Would you want to do research together with a major supply chain optimization software vendor? If so, you may be one of our new PhD students in the 'Learning and Explaining Supply Chain Optimization' project.

Job Description
Advances in OR have led to a broad industrial adoption of mathematical optimization technology to solve supply chain optimization problems. Despite that progress, two challenges remain that you would aim to address in this project. The first challenge is on solving real-life supply chain planning problems, where increasing scale and uncertainty are prime drivers leading to vulnerable plans and thus vulnerable supply chains. The second challenge is on seamless deployment and adoption of the optimization technology, where human planners who review the proposed plans do not understand these plans, the way they are generated and/or are unsure about their feasibility or quality.

Together with your fellow PhD students you would aim to develop combined AI and OR technology to learn how to find robust and efficient plans as well as combined Explainable AI and OR technology to learn how to make human planners understand and trust generated plans. The first goal holds, amongst others, the theoretical promise to provide practically polynomial-time solution methods for NP-complete problems. Under the P ≠ NP assumption, this is a massive challenge with a massive potential. For the second goal you would aim to help human planners understand the generated plans and the way they are generated, for example by ensuring that the mathematical definition of the planning problem matches the real-world problem and by supplementing proposed plans with AI-generated explanations that convince the human planner of their feasibility and quality.

The overarching objective of the project is to come to better and more robust supply chain optimization technology that is trusted by human planners so that high quality plans get fully adopted in practice. This increases the obtained benefits from supply chain optimization by i) having better plans that use scarce resources in a more robust and efficient way, leading to more robust supply chains, shorter delays, less waste, and lower carbon footprint and ii) improving its introduction and adoption, so that business practice follows the proposed plans and potential benefits materialize.

While focusing on one of the two challenges, you would be doing your research together with the DELMIA Operations Planning and Optimization (OP&O) R&D team and inside the Eindhoven Artificial Intelligence Systems Institute (EAISI). DELMIA OP&O is part of Dassault Systèmes (3DS) and is a market leader in solutions for modelling, planning, and optimization of business operations, providing solutions for planning of supply chains, manufacturing, logistics, workforce, or rail operations. EAISI brings together all AI activities of the Eindhoven University of Technology (TU/e). It is an institute where 300 academic staff and 600 PhD candidates from various departments do fundamental and applied AI research on the combination of and interaction between the domains of Data Science, Engineering Systems, and Humans and Ethics. EAISI focuses on AI systems where the physical, digital, and human worlds come together and aims to get to a better understanding, better designs, better models, and better decisions. One of the founding departments of EAISI is the Department of Mathematics and Computer Science, at which the proposed research shall be executed. You would be working with EAISI's Scientific Director prof.dr.ir. Wim Nuijten.

• A master's degree in Artificial Intelligence, Operations Research, Data Science, Computer Science, Mathematics, or a related field.
• Excellent coding skills (e.g. Python, PyTorch, Tensorflow).
• Fluent in written and spoken English (C1 level).
• Desire to conduct excellent research and publish in high quality conferences and journals.
• Ability and desire to collaborate and work in a multidisciplinary team.
• Ability to be self-propelling and drive your own research.
• Ability and desire to support teaching and to co-supervise bachelor and master students.

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.