Research Fellow
8 months ago
Key Responsibilities:
- Responsible for building ship simulation environments, developing global path planning algorithm and Deep Reinforcement Learning (DRL) learning models that can process to perform sea navigation task.
- Develop and implement a ship navigation simulation environment.
- Design and implement rule-based optimization algorithms such as A-Star, ant colony and genetic algorithm.
- Design and implement learning algorithms that can process input data and generate ship commands with confidence scores.
- Develop a human-machine interaction board to provide action recommendation for operator assistance.
- Conduct thorough research and contribute to the publication of research findings in top-tier conferences and journals.
Job Requirements:
- PhD degree in Computer Science or Electrical and Electronic Engineering or related fields
- Proficient programming skills and experience (Python, C++)
- Experience or knowledge in develop navigation frameworks
- Experience or knowledge in path planning algorithms such as such as A-Star, ant colony and genetic algorithm
- Experience or knowledge in Deep Reinforcement Learning and Graph Convolutional Neural Networks for collision avoidance
- Background in robotic motion planning research projects. (e.g., holonomic and non-holonomic motion models)
- Experience in developing and working with simulation environments, such as Gazebo, CARLA, or Unity
We regret to inform that only shortlisted candidates will be notified.
Hiring Institution: NTU
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