{"id":250041,"url":"https://alion.io/job/nanyang-technological-university-research-associate-robotics","title":"Research Associate (Robotics)","company":{"id":98222,"name":"Nanyang Technological University","domain":"ntu.edu.sg","url":"https://alion.io/company/nanyang-technological-university","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":77,"open_postings":194,"ghost_share":0,"stale_share":0.902,"repost_share":0,"time_to_fill_p50_days":45,"computed_at":"2026-11-03T05:54:40Z"}},"role":"Science & Research","role_family":"Science & Research","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":31000,"max_usd":76000,"period":"year","method":"role_country_seniority_unknown","sample_n":56},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Diffusion Models","optional":false},{"name":"Gazebo","optional":false},{"name":"Imitation Learning","optional":false},{"name":"Isaac Gym","optional":false},{"name":"Localization","optional":false},{"name":"Motion Planning","optional":false},{"name":"MuJoCo","optional":false},{"name":"Obstacle Avoidance","optional":false},{"name":"Path Planning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"robot_localization","optional":false},{"name":"ROS","optional":true}],"status":"live","first_seen_at":"2026-08-05T00:00:00Z","employer_posted_date":"2026-08-05","last_verified_at":"2026-11-03T17:11:52Z","board_verified":true,"closed_at":null,"days_open":90,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":90},"description":"School of Electrical and Electronic Engineering is one of the founding Schools of the Nanyang Technological University. Built on a culture of excellence, the School is renowned for its high academic standards and research. With over 3,000 undergraduates students and 2,000 graduate students it is one of the largest EEE schools in the world and ranks 4th in the field of Electrical & Electronic Engineering in the 2025 QS World University Rankings by Subjects.\nToday, the School has become one of the world’s largest engineering schools that nurtures competent engineers and researchers. Each year, the School graduates over a thousand students who are ready to take on great ambitions and challenges.\nFor more details, please view: https://www.ntu.edu.sg/eee\nThe project aims to develop robust, intelligent and efficient navigation systems for inspection robots, enabling autonomous localization, decision-making, motion planning and safe navigation in complex, dynamic real-world environments.\nThe Research Associate will support research on robot navigation, focusing on the integration of visual perception, localization, planning and navigation. The role will also investigate learning-based approaches, including diffusion models and reinforcement learning, for navigation decision-making, trajectory generation and adaptive robot behavior.\nKey Responsibilities:\nDesign and develop navigation algorithms for inspection robots in complex and dynamic environments.\n\nWork on global and local motion planning, obstacle avoidance, trajectory generation and trajectory tracking for humanoid robots.\n\nInvestigate diffusion models and diffusion-based policies for navigation planning, trajectory generation and action prediction.\n\nApply reinforcement learning and/or imitation learning methods to improve navigation performance and adaptive robot behavior.\n\nIntegrate visual navigation and planning modules with humanoid locomotion and whole-body control systems.\n\nBuild and evaluate algorithms in simulation environments and on real-world humanoid robotic platforms.\n\nContribute to publications and technical reports\n\nAssist in mentoring students and supporting research activities\n\nJob Requirements:\nMaster’s degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or related fields\n\nStrong background in at least one of the following:\nrobot motion planning and control;\n\nautonomous decision-making;\n\nrobot localization and navigation.\n\nExperience in one or more of the following:\npath planning, motion planning, trajectory optimization or model predictive control;\n\nreinforcement learning, imitation learning or learning-based control;\n\ndiffusion policies or generative decision-making;\n\nrobotics physics simulators (e.g., Isaac Gym, MuJoCo, Gazebo)\n\nProficiency in Python and/or C++\n\nExperience with PyTorch or similar deep learning frameworks\n\nStrong problem-solving ability and hands-on implementation skills\n\nWe regret to inform you that only shortlisted candidates will be notified.\nHiring Institution: 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