Research Scientist (Advanced Manufacturing and Semiconductor (AMS)), IHPC

The AMS Division, IHPC, A.STAR, is seeking a highly motivated Research Scientist to join a dynamic, multi-disciplinary team. This position is part of a joint laboratory initiative with an Oil&Gas company, focusing on the degradation behavior and reliability of polymeric seals in mechanically energized sealing systems used in oil and gas applications.

The successful candidate will play a key role in developing computational models, analyzing failure mechanisms, and enhancing the long-term reliability of polymeric sealing systems. This research is of strong industrial relevance and involves close collaboration with engineers and experimentalists from industry.

The key scope of work includes:

• Develop finite element (FE) models of mechanically energized sealing systems to evaluate performance and reliability under thermal, mechanical, and environmental loads.
• Automate FE-based parametric studies and perform sensitivity analyses to identify critical material and geometric factors affecting seal performance.
• Investigate failure modes such as viscoelastic relaxation, thermal aging, and thermal cycling develop and validate degradation models for these mechanisms.
• Integrate degradation models with traditional metrics (e.g., compressive stress relaxation, mechanical property evolution) for performance prediction.
• Work with experimental teams and partners to refine test procedures, define reliability criteria, and assess lifecycle failure risks.

Job Requirements

• PhD in Mechanical Engineering, Materials Science, Applied Physics, or a related field.
• Solid background in continuum mechanics, polymer material behavior (especially aging and viscoelasticity), and finite element modelling (FEM).
• Sufficient experiences in FE software (e.g., Abaqus) and Python scripting for automation and parametric studies experience with statistical FE analysis is a plus.
• Knowledge of polymer degradation mechanisms, aging tests, or reliability engineering methodologies is highly advantageous.
• Proficiency in scientific programming languages (Python, Fortran, MATLAB, or similar).
• Good communication and interpersonal skills to effectively collaborate across multidisciplinary teams and industrial partners.
• Proven ability to work independently, meet deadlines, and produce high-quality technical reports and publications.