PhD in Optimization for Resilient Transport Systems

Ntnu; Trondheim; Hybrid; NOK 522,000 - 638,000; Full time

Job summary

NTNU invites applications for a PhD candidate in Optimization and Decision Support for Resilient Transport Systems. The project develops optimization methods for multimodal transport, integrating dynamic models and machine-learning surrogates to evaluate many scenarios.

You will join STRIDE and collaborate across departments, with close interaction with industry partners, based in Trondheim for a 4-year PhD in Economic and Management sciences.

Qualifications

• Master’s degree in a relevant field with strong academic results (B or better on NTNU scale).
• Competence in mathematical optimization, operations research, and/or related quantitative methods.
• Excellent English oral and writing skills.

Responsibilities

• Conduct original scientific research related to the project topic.
• Develop optimization models and decision-support methods for resilient transport systems.
• Publish results in leading international journals and conferences.
• Collaborate with academic and industry partners.
• Integrate dynamic transport models and ML surrogates into optimization methods.
• Complete the required coursework as part of the PhD programme.
• Contribute to dissemination and communication of research results.

Skills

Mathematical optimization

Operations research

Quantitative methods

English proficiency

Education

Master's degree in Operations Research / optimization / applied mathematics / industrial engineering / transport or logistics

Job description

NTNU invites applications for a PhD candidate in Optimization and Decision Support for Resilient Transport Systems. The project develops optimization methods for multimodal transport, integrating dynamic models and machine-learning surrogates to evaluate many scenarios.

You will join STRIDE and collaborate across departments, with close interaction with industry partners, based in Trondheim for a 4-year PhD in Economic and Management sciences.