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A leading university in Singapore is seeking a Research Engineer to develop and train algorithms for visual navigation in mobile robots. The ideal candidate holds a Bachelor’s degree and has expertise in robot learning and reinforcement learning. Strong analytical skills and experience in C++ or Python are required. The position offers a 12-month contract with potential for extension based on performance.
Interested applicants are invited to apply directly at the NUS Career Portal.
Your application will be processed only if you apply via the NUS Career Portal.
We regret that only shortlisted candidates will be notified.
One Research Engineer position is open in the research group of Assistant Professor Zhao Lin, at the Department of Electrical and Computer Engineering, National University of Singapore (NUS).
The Research Engineer will work closely with the Principal Investigator (PI) on visual navigation foundation model for mobile robots, exploration using reinforcement learning control, learning-based control, etc.
The Research Engineer will develop and train algorithms that enable intelligent and robust autonomous navigation in unseen environments. Hardware experiments will be carried out to test and demonstrate the applications of the developed algorithms.
The initial appointment duration is 12 months, which can then be extended based on an evaluation at the end of the initial appointment.
The candidates should have a Bachelor’s degree from a reputable university, with expertise in robot learning, reinforcement learning, and aerial robotics.
A successful candidate should have a solid mathematical background (such as in calculus, linear algebra, ODE/PDE, optimization, real analysis, probability theory, stochastic process, etc). Strong publication records in leading journals and conferences of the relevant fields, and practical hands-on experience in applying visual foundation models to real mobile robots are required.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.