Job Description

Responsibilities

• Develop, implement, and validate autonomous ship navigation, collision-avoidance, and energy-efficient trajectory-planning algorithms for dynamic and constrained maritime environments.
• Develop physics-informed, data-driven, and control-oriented models for vessel manoeuvring, propulsion, energy consumption, and ship-performance assessment using simulation and full-scale operational data.
• Contribute to simulation and digital-twin platforms by integrating vessel models, environmental disturbances, onboard sensor data, and real-time control functions using ROS, MATLAB/Simulink, Python, or C++.
• Develop and evaluate situation-awareness functions, including sensor fusion, filtering, localisation, perception, and uncertainty analysis, to support safe autonomous vessel operations.
• Perform closed-loop simulation, software testing, debugging, and experimental validation of navigation and control algorithms, including model-scale or field demonstrations where applicable.
• Collaborate with multidisciplinary research teams, industry partners, and technology providers, and contribute to project deliverables, technical reports, proposals, and publications under funded research programmes.
• Perform other tasks as assigned by the supervisor.

Requirements

• PhD in Marine Technology, Naval Architecture, Ocean Engineering, Control Engineering, Robotics, or a related field.
• Experience in autonomous vessel navigation, collision avoidance, motion or trajectory planning, dynamic-system modelling, real-time control, or maritime energy optimisation.
• Experience with physics-informed, data-driven, grey-box, machine-learning, or system-identification methods using operational or sensor data is highly desirable.
• Strong programming skills in C++, Python, MATLAB/Simulink, or Linux, with experience in ROS, embedded systems, digital twins, or real-time simulation considered advantageous.