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Company Overview
The organisation is a collaborative research and innovation centre that works closely with industry partners to develop and deploy advanced manufacturing solutions. Operating within a strong public‑private partnership model, the centre focuses on driving industrial competitiveness through applied research, technology translation, and workforce capability development.
One of its core research groups specialises in smart virtual systems, leveraging artificial intelligence, optimisation techniques, and advanced modelling to enable intelligent, data‑driven decision‑making across modern manufacturing environments.
Role Overview
This role is suited for a motivated Scientist or Senior Scientist to lead and deliver research in modelling and optimisation for complex, enterprise‑level multi‑resource planning problems. The position offers the opportunity to push the boundaries of operations research while translating academic advances into practical, industry‑ready solutions across a diverse set of sectors.
The successful individual will bring strong technical expertise, the ability to lead research activities and project delivery teams, and excellent communication skills to engage both technical and business stakeholders. This role spans research leadership, project execution, and external collaboration, with a strong emphasis on real‑world impact.
Key Responsibilities
- Lead research and development of advanced optimisation algorithms addressing multi‑resource planning challenges such as production scheduling, capacity planning, and inventory optimisation.
- Collaborate closely with engineering teams to translate research outputs into deployable, industry‑ready systems.
- Define scientific research directions and develop innovative project proposals aligned with industry requirements.
- Drive competitive research funding applications and participate in collaborations with academic and industry partners.
- Publish research outcomes in leading international journals and conferences.
- Mentor junior researchers and contribute to long‑term research and capability roadmaps in enterprise optimisation.
Requirements
- PhD in Artificial Intelligence, Computer Science, Operations Research, or a related discipline, with a strong focus on optimisation, machine learning, or data science.
- Solid expertise in modelling and optimisation for planning and scheduling problems.
- Minimum of 3 years’ experience in research leadership and research project management.
- Proven capability in programming and algorithm development for optimisation and machine learning (e.g. Python, C#, .NET).
- Strong publication record in high‑quality international journals and conferences.
- In‑depth understanding of production planning, scheduling, and inventory optimisation domains.
- Excellent written and verbal communication skills, with the ability to present complex ideas clearly.
- Demonstrated experience applying optimisation techniques to real‑world, multi‑resource industry problems (industry project experience is advantageous).
