Job Description

This position involves working on a project related to advanced variants of the multi-robot search problem. With the rapid development of affordable robots with embedded sensing and computation capabilities, we arequickly approaching a point at which real-life applications will involve the deployment of hundreds, if notthousands, of robots. Among these applications, significant research effort has been devoted to multi-agentsearch, where deploying numerous agents can greatly improve the time-efficiency and robustness of search.The objective of this position includes contributing to the model development, solution, and implementation ofnovel multi-agent search/coverage methods using advanced AI tools such as distributed reinforcementlearning. These models, once trained, will also be validated and tested in simulation against state-of-the-artbaselines. The role involves the opportunity to work with the research team within the Mechanical Engineeringdepartment at the National University of Singapore. The successful candidate will be self-motivated with anoutstanding track record in computer science, robotics, machine learning (in particular, reinforcementlearning), or related disciplines.

The main research tasks for the project include but will not be limited to:

• Developing novel decentralized multi-agent search methods for advanced problems, based on local sensingand decision-making only, and by relying on/extending recent reinforcement learning tools.
• Testing the devised models against state-of-the-art methods in standard simulation-based benchmarks.
• Coordinating a small team of researchers at different levels (e.g., FYP students, remote/on-site interns,master's students).
• Write papers and present work at top-tier local or international conferences or workshops.

Qualifications

• BEng/BSc/MEng/MSc in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or relateddisciplines.
• Experience in developing decentralized controllers using recent reinforcement learning methods, as well asmore conventional baselines, and performing systematic comparisons and testing.
• Proficiency with GNU/Linux, Python/C++ and at least one of the main machine learning libraries (e.g.,tensorflow, keras, pytorch).
• Excellent interpersonal and communication skills.
• Good teamwork abilities, self-motivation and self-reflection.
• Proficiency in English language, both in oral and written form.

More Information

Location: Kent Ridge Campus
Organization: Engineering
Department: Mechanical Engineering
Employee Referral Eligible: No
Job requisition ID: 7531