Data-Driven Autonomous Shipping & Port Operations Postdoc

Delft; Delft; On-site; EUR 45,000 - 60,000; Full time

Benefits offered by this job

ABP pension

Health insurance discounts

Education & training opportunities

Dual Career Programme

Relocation assistance

Job summary

TU Delft's Faculty of Mechanical Engineering invites applications for a Postdoc on Data-Driven Autonomous Shipping and Port Operations. You will develop data-driven and model-based methods to integrate autonomous vessels into maritime transport and port logistics, using vessel, sensor and traffic data to analyze operational complexity and to propose CONOPS for navigation and energy management.

The role involves port-call optimisation, agent-based modelling, and evaluating collaboration

Qualifications

• PhD degree in a relevant field with strong data engineering and quantitative modelling skills.
• Experience with autonomous shipping, port logistics or decision-support systems is an asset.
• Excellent spoken and written English, ability to collaborate with project partners and research institutes.

Responsibilities

• Develop data-driven and model-based approaches for integrating autonomous vessels into maritime transport and port logistics.
• Analyze data from vessels, sensors, environments and traffic to understand operational complexity and CONOPS.
• Contribute to architecture, management and use of the data platform supporting these activities.
• Focus on port-call optimisation and logistics ecosystem strategies for autonomous vessels; identify inefficiencies and propose improvements.
• Use agent-based modelling and scenario analyses to evaluate collaboration strategies among ships, terminals and logistics actors.

Skills

data engineering

quantitative modelling

communication skills

Education

PhD in mechanical engineering / maritime tech / OR / systems & control

Job description

TU Delft's Faculty of Mechanical Engineering invites applications for a Postdoc on Data-Driven Autonomous Shipping and Port Operations. You will develop data-driven and model-based methods to integrate autonomous vessels into maritime transport and port logistics, using vessel, sensor and traffic data to analyze operational complexity and to propose CONOPS for navigation and energy management.

The role involves port-call optimisation, agent-based modelling, and evaluating collaboration