Research Engineer (Visual Navigation Model)

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 50,000 - 70,000; Full time

Job summary

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.

Qualifications

• A min Bachelor’s degree in relevant fields.
• Research experiences in computer vision and reinforcement learning.
• Proficient in C++ or Python and familiar with machine-learning tools.

Responsibilities

• Develop and train algorithms for autonomous navigation.
• Conduct hardware experiments to test algorithms.
• Collaborate with the Principal Investigator on research.

Skills

Robot learning

Reinforcement learning

C++

Python

Computer vision

Control theory

Analytical problem-solving

Education

Bachelor’s degree in Computer Engineering/Science or related fields

Tools

Machine-learning tools and packages

3D simulation environments

ROS

Job description

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.

Job Description

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.

Qualifications

• Possess a min Bachelor’s degree in Computer Engineering/Science or strictly related (e.g., either Electrical Engineering, Mathematics, Communication, Mechanical, etc.)
• Have research experiences in computer vision, vision foundation model, control theory, reinforcement learning.
• Possess a strong academic record proved through coursework (especially math-intensive courses) and projects during his/her undergraduate and master’s studies.
• Proficient in C++ or Python. Familiar with machine-learning tools and packages. Familiar with various 3D simulation environments for quadrotor simulations. Familiar with ROS and quadrotor control algorithms.
• Have well-established analytical and problem-solving skills, as documented by publications that are relevant to the field of robot navigation, reinforcement learning control for robotics applications.
• Excellent communication skills as he/she is required to publish and present results at conferences and journals independently.
• Prior activity performed in world-class research environments is highly valued.
• Open to Fixed Term Contract.