Deskripsi Pekerjaan
Join A*STAR's DMD/SVS division as a Senior Research Engineer and spearhead groundbreaking AI-driven planning and scheduling solutions. You'll develop cutting-edge tools that optimize complex industrial operations, collaborating with world-class researchers to transform theoretical algorithms into practical systems. This role offers the opportunity to pioneer next-generation AI applications in high-impact domains like manufacturing logistics and resource allocation. Your work will directly influence how organizations worldwide manage dynamic scheduling challenges in real-time environments. A*STAR provides state-of-the-art research infrastructure and a multidisciplinary ecosystem where innovation thrives. If you're passionate about bridging advanced AI research with industrial applications, this is your chance to shape the future of intelligent automation systems.
Tanggung Jawab
- Lead development of AI-powered planning and scheduling algorithms for industrial optimization
- Design and implement scalable solutions for real-time resource allocation systems
- Collaborate with cross-functional teams to translate business requirements into technical specifications
- Conduct rigorous testing and validation of scheduling models in simulated and live environments
- Publish research findings in peer-reviewed journals and industry conferences
- Mentor junior researchers and drive innovation through experimental research initiatives
- Optimize algorithm performance for computational efficiency and solution quality
Kualifikasi
- PhD or Master’s degree in Computer Science, AI, Operations Research, or related field
- Minimum 5 years experience in AI/ML algorithm development for scheduling or optimization
- Expertise in constraint programming, metaheuristics, or reinforcement learning techniques
- Proficiency in Python, C++, and relevant frameworks (PyTorch, TensorFlow, OR-Tools)
- Strong background in combinatorial optimization and discrete event simulation
- Proven track record of publishing in top-tier AI/operations research venues
- Experience with cloud-based deployment of scheduling systems (AWS/Azure/GCP)