About the role
AI summarisedSenior research scientist role at ARTC's Smart Virtual Systems group focused on AI/ML-driven optimisation and simulation for complex manufacturing challenges. Leads research translating academic innovations into deployable industrial solutions for MNCs and local companies.
ResearchOnsite
Key Responsibilities
- Lead and collaborate with other scientists on research integrating AI/ML, mathematical optimisation, and digital simulation to address industry-driven operational challenges, including production scheduling, operations planning, capacity planning, and process optimisation
- Work with research engineers to translate research outcomes into deployable industrial solutions
- Develop competitive research proposals and foster collaborations with industry and academic partners (e.g., MNCs, IHLs, other research institutes)
- Publish at leading academic journals and conferences to contribute A*STAR's reputation as a leading R&D organisation
- Mentor junior researchers and students in scientific methods and research professionalism
Requirements
- PhD in Computer Science, Industrial Engineering, Operations Research, or a related field with a focus on optimisation, simulation, AI/ML, or data science
- 3+ years of post-PhD research experience (Senior Scientist level)
- Strong knowledge of production scheduling, operations/capacity planning, and inventory/sourcing analytics in manufacturing contexts
- Solid background in simulation (e.g., DES), mathematical optimisation (e.g., exact methods, meta-heuristics, surrogate-based algorithms), and AI/ML (e.g., reinforcement learning, genetic programming)
- Proficiency in Python for programming and algorithm development; C#/.NET or software engineering experience is advantageous
- Experience addressing real-world industry problems
- Strong publication record in top-tier journals and conferences
- Excellent verbal and written communication skills across technical and business audiences
- Positive, proactive mindset with the ability to collaborate and influence across multidisciplinary stakeholders