Research Scientist in Experimental Aerodynamics
Applications are invited for the position of Research Scientist to contribute to experimental research in aerodynamics. Candidates should hold a Doctoral degree in Mechanical Engineering, Aeronautical Engineering, or a closely related discipline, with a strong foundation in fluid dynamics.
At the National University of Singapore (NUS), the successful applicant will join a large, highly motivated research group focused on experimental measurements and numerical simulations across a broad range of aerodynamics and fluid mechanics problems. The position offers access to extensive high-performance computing resources at NUS and the National Supercomputing Centre, as well as state-of-the-art experimental facilities and instrumentation.
The appointee will be expected to actively disseminate research outcomes by leading the preparation of manuscripts for peer-reviewed journals, presenting findings at international conferences, and showcasing results at other appropriate forums. The role also involves supporting project-related administrative duties, including risk assessments, coordination of project meetings, and research documentation, as well as any other responsibilities assigned by the line manager following consultation with the post holder.
Essential skillsets
- Strong experience and understanding of aerodynamics and/or fluid mechanics
- Background in one or more of the following areas: bluff-body flows, airfoils, active and passive flow control, boundary-layer flows, multiphase flows, and bio-inspired aerodynamics
- Good hands-on skills and practical experience in designing and assembling experimental test rigs and in wind tunnel testing
- Demonstratable prior experience in experimental techniques such as hot-wire CTA, particle image velocimetry, load cell and/or external force balance, wake rake, oil film interferometry, tuft flow and smoke flow visualisation, etc.
- Experience in programming using MATLAB or similar languages for data post-processing and analysis
- Ability to work independently and as part of a team
- Good written and oral communication skills
Desirable skillsets
- Experience in applying machine learning techniques to engineering or scientific problems
Applications with full CV are to be submitted electronically to:
Dr CHEW, Siou Chye, email: tslchew@nus.edu.sg
Dr TAY, Chien Ming Jonathan,, email: tsltcm@nus.edu.sg
Dr LIM, Haoxiang Desmond, email: d.h.lim@nus.edu.sg
Only shortlisted applicants will be notified.
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