About this role
This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. Video: https://youtu.be/Xt-yHCN5QS0 About the position We invite applications for a PhD Candidate position focused on the development of hybrid artificial intelligence and optimization methods for dynamic and stochastic transport operations. The position is based at the Department of Industrial Economics and Technology Management, located at NTNU’s campus in Trondheim. This is an educational position, which will provide promising research recruits the opportunity for professional development through studies towards a PhD-degree. The position is connected to the PhD program at the Faculty of Economics and Management, and the faculty will be your employer. Transport and logistics systems are becoming increasingly complex, data-rich, and dynamic. Public transport operators, freight carriers, and logistics providers must make decisions under uncertainty while responding to disruptions, fluctuating demand, and changing operating conditions. This PhD project focuses on developing AI-supported decision methods for routing and scheduling in transport and logistics systems. The research investigates how operations research and artificial intelligence can be combined to improve planning and operational decision making under uncertainty. The project addresses challenges that arise when traditional optimization models are applied in real-world settings characterized by large-scale networks, stochastic demand, operational disruptions, and complex constraints. A central research question is how machine learning can be integrated with optimization algorithms to support faster, more robust, and more adaptive decision making. The project addresses research questions like: How can learning-based models be integrated with optimization methods to improve the robustness and performance of transport planning decisions? How can hybrid AI–optimization methods scale to large real-world transport and logistics systems while handling the many constraints encountered in practice? How can routes and schedules be evaluated efficiently across many possible future scenarios to support both tactical planning and real-time adaptation? To address these questions, the PhD candidate will develop and evaluate new decision-support methods that combine optimization and machine learning. Particular attention will be given to methods that can rapidly assess the consequences of routing and scheduling decisions under uncertainty, enabling both robust planning and adaptive operational decision making. The research will be developed and validated using real-world transport and logistics applications. The primary application domain is public transport planning in collaboration with AtB, the public transport authority in the Trondheim region. Additional case studies may be conducted together with other logistics partners, including Posten Bring (Norway's national postal and logistics operator), Bama (Norway's largest fruit and vegetables distributor), and Oda (Norway's leading online grocery retailer). The position offers a unique opportunity to work at the intersection of artificial intelligence, optimization, and transport systems while contributing both fundamental methodological advances and practical decision-support tools. Research environment The PhD position is part of the Norwegian Centre on AI for Decisions (aiD), https://aid-centre.no/ , a national research initiative led by NTNU and SINTEF. The centre brings together around 60 partners [MS1] from academia, research institutes, industry, and the public sector. Through aiD, the PhD project will be connected to a larger research environment working on hybrid AI–optimization methods for planning and operations under uncertainty, as well as applications in logistics, healthcare, energy systems, and infrastructure planning. The PhD candidate will be hosted at the Managerial Economics, Finance and Operations Research (BEDØK) group at the Department of Industrial Economics and Technology Management. The group is one of Norway's leading academic environments in operations research, logistics, optimization, and quantitative decision support. In addition, the PhD candidate will work in close collaboration with researchers from SINTEF Digital’s Optimization group, a leading research environment in applied optimization and artificial intelligence. The department endeavors to promote research that meets high international standards. Consequently, collaboration with international institutions is considered important. The department therefore encourages the successful PhD candidate to spend one or two semesters of the contract period at a foreign educational institution. The department offers support in planning such research visits. The mission of Department of Industrial Economics and Technology Management (IØT) is to carry out education, research, and innovation activities at an international level at the intersection between technology/natural sciences and business economics, management, and HSE. The department’s activities aim to contribute to sustainable value creation within technology-based areas in industry, business, and the public sector in Norway. Your role in the project The PhD candidate will: Conduct original scientific research related to the project topic Develop new algorithms and methods combining AI and optimization Publish research results in leading international journals and conferences Collaborate with academic and industry partners Participate in aiD centre activities and research meetings Complete the required coursework as part of the PhD programme Contribute to dissemination and communi