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.
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 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:
Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.
Do you recognize yourself in this profile and would you like to know more? Please contact
the hiring manager prof.dr.ir. Wim Nuijten (w.p.m.nuijten[at]tue.nl).
Visit our website for more information about the application process or the conditions of employment. You can also contact HRServices.MCS[at]tue.nl.
Are you inspired and would like to know more about working at TU/e? Please visit our career page.
We invite you to submit a complete application by using the apply button. The application should include a:
• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references.
We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.