(apologies for multiple posting)

https://jobs.tue.nl/en/vacancy/phd-on-datadriven-optimization-for-sustainabl...https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fjobs.tue.nl%2Fen%2Fvacancy%2Fphd-on-datadriven-optimization-for-sustainable-lastmile-delivery-878199.html&data=04%7C01%7C%7C82342ebea79d4efb362008d919d7e835%7Ccc7df24760ce4a0f9d75704cf60efc64%7C1%7C0%7C637569237377515994%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=4Wyjf%2BA%2BVqsiyro052d7KGmkEzg6DZoBmxZZfCNPqxk%3D&reserved=0

The “Atlas leefbare stad” (Atlas livable city) is a digital twin application that processes logistical data for urban environments. It helps policymakers to gain insight into the current logistical situation, but it can also be used to find the optimal decision with respect to an objective such as fuel consumption or greenhouse gas emission. This makes it possible to try new optimal solutions in a realistic virtual environment, before applying them in practice. As a PhD candidate, you are expected to develop new machine learning driven optimization algorithms, using techniques such as reinforcement learning, online supervised learning, Bayesian optimization, etc., that can handle such a complex data-based environment. Different research goals such as incorporating expert knowledge in the data-driven models and designing objective functions and uncertainty measures that are easy to learn and to optimize, make this a challenging project and require a mix of applied and theoretical research.