About the Role
Our client is seeking a highly motivated Scientist or Senior Scientist to lead and conduct research in advanced planning, scheduling, modelling, and optimization for complex manufacturing systems. The successful candidate will work closely with our client's industry partners to translate research into deployable solutions and is expected to be independent and initiative-driven, with a demonstrated ability to develop innovative solutions to challenging industrial problems.
This posting covers two levels — Scientist and Senior Scientist — differentiated by experience and scope of responsibility, as outlined below. Applicants should indicate which level they are applying for based on their experience.
Key Responsibilities (Both Levels)
Conduct research into innovative optimization approaches for complex planning and scheduling problems, including flexible job shop scheduling.
Develop mathematical models and optimization approaches for complex, large-scale scheduling problems involving multiple machines, resources, and practical manufacturing constraints.
Collaborate with a team of engineers to translate research outcomes into practical, deployable solutions across various industry sectors, particularly in planning and scheduling.
Engage directly with our client's industry partners to understand real-world planning/scheduling challenges and align research direction accordingly.
Formulate scientific research directions and innovative proposals aligned to industry needs, to secure competitive funding.
Contribute to peer-reviewed publications and technical presentations as part of ongoing research output.
Additional Responsibilities — Senior Scientist
Provide technical leadership and mentorship to junior scientists and engineers within the research team.
Lead the formulation and execution of funded research projects, including proposal development and stakeholder management.
Serve as a technical point of contact for industry partners on planning/scheduling engagements.
Job Requirements
Scientist
PhD in AI, Computer Science, Operations Research, or a related discipline, with emphasis on optimization, planning, scheduling, or related areas.
0–3 years of post-PhD research experience (industry or academic).
Strong modelling and optimization background; experience in flexible job shop scheduling or related problems is an advantage.
Programming/coding skills in developing optimization algorithms.
A track record of scientific publications in reputable journals or conferences.
Good understanding of the planning and scheduling domain.
Strong technical presentation and writing skills.
Senior Scientist
PhD in AI, Computer Science, Operations Research, or a related discipline, with emphasis on optimization, planning, scheduling, or related areas.
5+ years of post-PhD research experience, including demonstrated leadership of R&D projects.
Proven track record of applying optimization algorithms to real-world planning and scheduling problems.
Experience securing competitive research funding (grant writing, proposal leadership) is highly desirable.
Strong programming/coding skills in developing optimization algorithms.
Strong record of scientific publications in top-tier journals or conferences.
Deep understanding of the planning and scheduling domain, with experience translating research into industry-deployed solutions.
Excellent technical presentation and writing skills; experience presenting to industry stakeholders preferred.
Cygnify Singapore, Singapore, SGP Office
Singapore, Singapore
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