Phd in Data-Driven Optimization Models and Algorithms for Production Planning and Scheduling in Flexible Manufacturing Systems: ISyE (Ghent University, Belgium)
ISyE is a core research group of Flanders Make. It performs applied research in the domain of industrial systems engineering and optimization. Our major research areas are in flexible assembly systems design, control and optimization, and in particular production and maintenance planning and scheduling.
Outline of the Phd:
The availability of data, usually generated by numerous sensors embedded in both the assembled products as well as in the assembly processes, offers an extraordinary opportunity for the development of data-driven robust optimization models and algorithms to many industrial engineering optimization problems. The goal of this PhD research work is to develop innovative data-driven robust optimization models as well as their corresponding solution algorithms for planning and scheduling problems in flexible manufacturing systems. In particular, we will investigate flexible assembly systems characterized by a large number of variants produced in low-volume and involving manual as well as automated assembly tasks. The research work will be carried out in close collaboration with industry. This will grant us access to data and a number challenging industrial use cases.
We offer the opportunity to carry out a doctoral research with a scholarship in a pleasant environment (ISyE-core lab, part of Ghent University and Flanders Make).
Highly creative and motivated PhD student with the following qualifications:
- You have a strong interest in applied Data-Driven stochastic optimization and are eager to advance the state-of-the-art in this domain.
- You earned a master degree (or in the process of earning it by the end of academic year 2020-2021) in Industrial Engineering, Operations Research, Applied Mathematics, Computer Science, or equivalent, with excellent achievement.
- You have a good knowledge of optimization and strong computer science skills (python, Julia, C++, or other). Experience with algorithmic approaches or programming frameworks are considered as significant plus.
- You are motivated to validate and transfer your findings to industry.
- You have strong communication skills and your English is fluent, both speaking and writing.
How to apply
Send your application by email or any questions concerning this vacancy to prof. E.-H. Aghezzaf (email@example.com ), indicating “Application: PhD Data-Driven Optimization for Planning and Scheduling in FMS” in the subject. Applications should include (1) an academic resume, (2) a personal motivation letter, and (3) detailed transcripts of study results. After a first screening, selected candidates will be invited for an interview (via Teams, Skype, Zoom) as a first contact in a multi-stage selection process.
- Application deadline: July 16th 2021 or until the vacancy is filled.
- Type of contract: Full-time
- Employment: Temporary (4 years), with yearly progress evaluation
- Earliest starting date: September 2021
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