JOB DESCRIPTION

This post-doctoral position makes fundamental advances in infrastructure planning and scheduling under uncertainty. These advances will be applied to modelling of supply chain scenarios for offshore wind farm installation, including optimised planning schemes.
Researchers at TU Delft have developed design approaches that account for many different perspectives in major infrastructure projects including offshore wind farms. These perspectives include manufacturing of parts, storage and transport capacity limitations, port congestion and strong dependence on weather conditions. You will further develop and push towards application such approaches, to support the development of supply chain scenarios for wind farm installation. You will lead optimisation of planning schemes for several practical cases, including the development of decision rules for the mitigation of disruptions.
Relevant approaches or experience may include planning and scheduling under uncertainty, reinforcement learning, (distributionally) robust optimisation, uncertainty quantification, multi-objective optimisation, and evolutionary algorithms.
The successful applicant will join the STAR Lab at the Faculty of Engineering, Mathematics and Computer Science, working with Sequential Decision Making group in the same faculty, and be connected to researchers in the Faculty of Civil Engineering and Geosciences.
This research is part of the project ‘Efficient From Fabrication to Installation of Large Offshore Assembled Turbines’ funded by the Netherlands Enterprise Agency (RVO). As part of the project, you will work with industrial partners including Boskalis.

JOB REQUIREMENTS

When you start this postdoc position:

• You hold a PhD degree or have submitted your PhD dissertation.
• You are excited to make and apply fundamental advances in (AI) algorithms.
• You want to lead research and define approaches to the challenges in the project.
• You are able to work independently and also as part of a team with other researchers.
• You are able to communicate with diverse stakeholders including industrial partners.
• You have fluency in written and spoken English.

Please refer the Job description for details