Research Fellow (Multi-UAVs Path Planning)

Nanyang Technological University Singapore; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A higher education institution in Singapore is seeking a Research Fellow for Multi-UAVs Path Planning. The role involves developing algorithms for advanced path planning and ensuring efficient navigation in complex environments. Ideal candidates should hold a Ph.D. with strong research backgrounds in relevant fields and programming experience, particularly in Python and C++. This full-time position is expected to last approximately one year, providing the opportunity to work with cutting-edge research facilities.

Qualifications

• Ph.D. in Robotics, Computer Science, Electrical Engineering, or related fields.
• Strong research background in path planning, motion planning, and multi-robots coordination.
• Proficiency in Python and C++, with experience in ROS/ROS2.

Responsibilities

• Develop advanced path planning algorithms for multi-UAV systems.
• Design and implement collision-free navigation strategies.
• Validate algorithms in both virtual and real-world scenarios.

Skills

Path Planning

Proficiency in Python

Proficiency in C++

ROS/ROS2 experience

Communication skills

Education

Ph.D. in Robotics or related fields

Tools

Gazebo

Unity3D

Job description

Research Fellow (Multi-UAVs Path Planning)

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Research Fellow (Multi-UAVs Path Planning)

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Join to apply for the Research Fellow (Multi-UAVs Path Planning) role at Nanyang Technological University Singapore

The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE prides itself in its excellent research capabilities in areas including advanced manufacturing, aerospace, biomedical, energy, industrial engineering, maritime engineering, robotics, etc. The school is equipped with state-of-the-art research infrastructure, housing a comprehensive range of cluster laboratories, test bedding facilities, research centres/institutes and corporate laboratories. Cutting-edge research in MAE addresses the immediate needs of our industries and supports the nation’s long-term development strategies. In the new era of industrial 4.0 and sustainable living, MAE is rigorous in developing new competencies to support the growth and competitiveness of our engineering sector in the global landscape. MAE has grown to be leader in Engineering Research, ranking amongst the top engineering schools in the world.

For more details, please view https://www.ntu.edu.sg/mae/research.

About

We welcome applications for a Research Fellow position in Multi-UAVs Path Planning at the School of Mechanical and Aerospace Engineering at Nanyang Technological University, Singapore. This is a full-time appointment funded for about a 1 year (depends on hiring date). The selected candidate will join a group equipped with state-of-the-art facilities to work on the following:

• Developing advanced path planning, search, and exploration algorithms for multi-UAVs systems in unknown and complex 3D environments.
• Designing efficient obstacle avoidance strategies to ensure collision-free navigation in dense settings.
• Implementing and validating algorithms in both virtual and real-world scenarios to optimize performance in indoor and outdoor environments.
  
  

Mandatory Requirements

• Ph.D. in Robotics, Computer Science, Electrical Engineering, or related fields, with a focus on Path Planning, Multi-Robot Systems, or Autonomous Navigation.
• Strong research background in path planning, motion planning, and multi-robots coordination in complex environments.
• Proficiency in Python and C++, with extensive experience in ROS/ROS2 for robotic development.
• Familiarity with popular path planning algorithms such as RRT, A*, and optimization-based methods.
• Hands-on experience with simulation environments such as Gazebo and Unity3D.
• Excellent verbal and written communication skills in English for research work
  
  

Preferred Requirements

• Experience with deep learning and reinforcement learning algorithms in robotic decision.
• Familiar with UAV kinematics and dynamics.
  
  

We regret to inform that only shortlisted candidates will be notified.


Hiring Institution: NTU

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Research, Analyst, and Information Technology

• Industries

  Higher Education

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