Role overview
- Conduct a thorough review of relevant academic methods (e.g., sophisticated metaheuristics, large neighborhood search, advanced restart strategies) that can effectively deal with complex local optima in scheduling
- Select one or more promising techniques, implement them as a proof-of-concept within our existing optimizer environment and test their performance on real-world datasets
- Analyze the current optimizer behavior, identify specific scenarios leading to local optima, and develop innovative methods to address these limitation
- Document your research and results, providing clear, evidence-based recommendations for potential integration into the core system
- Collaborate closely with the R&D team and contribute to discussions on optimization improvements and industrial applications
What we're looking for
- Currently pursuing a Master’s degree in Operations Research, Computer Science, Econometrics, (Applied) Mathematics, or a related field
- A strong foundation in optimization theory, algorithms, operations research, and data structures with a strong interest in scheduling
- Proficiency in at least one (object-oriented) programming language (C++, Java, or Python preferred)
- Strong communication skills in English
- Analytical mindset and proactive approach to problem-solving
As a game-changer in sustainable technology and innovation, Dassault Systèmes is striving to build more inclusive and diverse teams across the globe. We believe that our people are our number one asset and we want all employees to feel empowered to bring their whole selves to work every day. It is our goal that our people feel a sense of pride and a passion for belonging. As a company leading change, it’s our responsibility to foster opportunities for all people to participate in a harmonized Workforce of the Future.
Tags & focus areas
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