Education Requirements:

• Master or Ph.D. degree in computational cognitive science, robotics, machine learning, applied mathematics, statistics, or related fields

Experience Requirements:

• Proven publication track record at conferences such as ICML, NeurIPS, ICLR, AAAI, ICRA, IROS, TPAMI, IJRR, etc.

• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)

Other Requirements:

• Strong interest in one or multiple of the following topics: Multi-agent task planning and collaboration

• Strong interest in Multi-agent systems, predictive multi-agent systems

• Strong interest in Video understanding: human activity recognition and intent prediction

• Strong interest in Reinforcement learning, multi-agent reinforcement learning

• Strong interest in Algorithmic game theory

• Strong interest in Theory of mind, Bayesian cognitive science

• Strong interest in Physical and social interaction, human communications

• Broad understanding of the full machine vision pipeline from sensors to high-level algorithms

Responsibilities:

• Invent, analyze, design, develop and optimize multi-agent planning algorithms

• Collaborate in a team environment across multiple scientific and engineering disciplines, making the architectural trade-offs required to rapidly deliver software solutions

• Write clean readable code, debug complex problems that span systems, prioritize ruthlessly and get things done with a high level of efficiency

• Learn constantly, dive into new areas with unfamiliar technologies

Experience Requirements:

• At least two years’ experience in designing and conducting robotics-related projects

Other Requirements:

• Strong hand-on skills with proficiency in at least one of the fields: CAD design (AutoDesk, Solidworks, etc.); PCB design; CNC machine operations; Electric or hydraulic motor development and control (For hardware)

• Strong programming skills with proficiency in at least one of the fields: ROS; Embedded systems; Deep learning using PyTorch or Tensorflow (For software)

• Strong interest in one or multiple of the following topics: Control and Estimation

• Strong interest in SLAM

• Strong interest in Robot Design and Dynamic Modeling

• Strong interest in Multi-robot and Swarm Systems

• Strong interest in Machine Learning, including Deep Learning, Imitation Learning, Reinforcement Learning etc.

• Strong interest in Perception, including Computer Vision, Tactile Perception, Audio Perception, Robot Dialogue

• Strong interest in Cognitive Robot and Human-robot Interaction

• Strong interest in Task and Motion Planning

• Strong interest in Other related fields in Robotics