Job Description

Contribute to the virtual testing and validation platform of Maritime Autonomous Surface Ships (MASS), focusing on virtual environment creation, collision detection and collision avoidance (CDCA), motion prediction, and regulatory compliance.

Develop and implement control algorithms within simulation environments to evaluate system performance and safety.

Support model-scale experiments in the TCOMS ocean basin, including test planning, execution, data analysis, and iterative refinement of assurance methodologies.

Work with industry partners, classification societies, and research institutes to ensure MASS functions comply with the IMO MASS Code, COLREGs, and safety standards.

Contribute to the preparation of grant proposals, technical reports, and publications aligned with TCOMS? strategic objectives.

Perform additional tasks assigned by the supervisor



Requirements



Master/PhD degree in Transportation Engineering, Naval Architecture, Mechanical Engineering, Computer Engineering, or a related field

Demonstrated expertise in transportation network, vessel dynamics, or autonomous control systems.

Proficiency in MATLAB/Simulink, Python, or C++ for system modelling and validation.

Strong analytical and problem-solving skills in a multidisciplinary R&D environment.

Effective interpersonal and communication skills to liaise with regulators, industry partners, and researchers.

Self-driven, adaptable, and committed to professional integrity.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.

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