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(Senior) Scientist, DMD/SVS (ARTC)

A*STAR RESEARCH ENTITIES
Islandwide, Full Time
POSTED ON 4/24/2025 CLOSED ON 4/24/2025

Job Posting for (Senior) Scientist, DMD/SVS (ARTC) at A*STAR RESEARCH ENTITIES

The Advanced Remanufacturing and Technology Centre (ARTC) is a public-private partnership consortium of more than 80 industry members. Our core mission is to develop and deploy advanced manufacturing solutions and upskill the workforce to drive local industry competitiveness.

Smart Virtual Systems (SVS) Group is seeking a highly motivated Scientist/ Senior Scientist to lead and conduct research in modelling and optimization of enterprise multi-resource planning. He/she is expected to be independent and initiative-driven, demonstrating the capacity to discover innovative solutions to challenges.

The key roles & responsibilities include:

  • Research into innovative optimization algorithms to efficiently solve multi-resource planning problems, including production scheduling, inventory management and production capacity planning
  • Work with a team of engineers to translate research outcomes to practical solutions for various industry sectors
  • Formulate scientific research directions and innovative proposals aligned to industry needs to secure competitive funding

Job Requirements

  • PhD degree in AI, Computer Science, Operations Research, or other relevant disciplines with emphasis on optimization, machine learning and data-science
  • Candidate with experience in modelling and optimization are welcome to apply
  • 3 years’ experience in research and leadership of R&D projects in the relevant area of expertise
  • Experience in research and leadership of R&D projects in the relevant area of expertise will be an added advantage
  • Programming/coding skills in developing optimization and machine learning algorithms
  • Good track record of scientific publications in top journals or conferences
  • Good understanding of the production planning &scheduling domain
  • Excellent technical presentation and writing skills
  • Proven track record in applying optimization algorithms to multi-resource planning problems is a plus
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