Join to apply for the
Research Engineer (Differentiable Simulation)
role at
National University of Singapore
Overview
The project centers on advancing high-performance computation and creating differentiable simulation frameworks tailored for robotic learning.
Responsibilities
Develop physics-driven differentiable simulators that support robotic learning and manipulation tasks, including rigid body mechanics, soft-body interactions, and fluid dynamics.
Implement GPU-based forward and differentiable simulation engines, ensuring high computational efficiency and optimized performance for large-scale robotic experiments.
Formulate control policies for robotics by integrating differentiable simulators with complementary machine learning strategies, exploring scalability for deployment in complex robotic systems.
Qualifications
Min Bachelor’s degree in Electrical/Electronic Engineering, Computer Engineering, Computer Science, or a closely related field.
Strong background in computer graphics and robotics, with emphasis on physics-based simulation, differentiable simulation, and high-performance computing.
Hands-on experience with automatic differentiation libraries (e.g., JAX, AutoGrad, Warp, Taichi).
Skilled in GPU programming, with knowledge of CUDA thread scheduling, memory allocation, and performance tuning.
Experience managing large-scale CUDA projects and utilizing CudaGraph is highly valued.
Proficiency in software development using C++ and Python, with familiarity with Cloud and Edge Computing environments.
Strong analytical mindset and advanced computational problem-solving abilities.
Understanding of software engineering practices; contributions to open-source software are considered an advantage.
Self-driven and proactive, capable of independent work while excelling in team collaboration.
A curious mindset and willingness to push boundaries are essential.
Open to Fixed Term Contract.
More Information
Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department: Electrical and Computer Engineering
Employee Referral Eligible: No
Job requisition ID: 30497
Job Details
Seniority level: Not Applicable
Employment type: Full-time
Job function: Engineering and Information Technology
Industries: Higher Education, Education Administration Programs, and Strategic Management Services
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