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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-yHCN5QS0About 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 communication of research results
Required selection criteria
Applicants must hold a master’s degree in a relevant field with strong academic results (B or better according to NTNU’s grading scale). Relevant academic backgrounds include:
- Operations research
- Computer science
- Artificial intelligence or machine learning
- Applied mathematics
- Engineering disciplines with strong quantitative and algorithmic content
Applicants must document competence in optimization, operations research or machine learning.
PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application”.
The appointment is to be made in accordance with NTNUs guidelines for recruitment positions for general criteria for the position.
Preferred selection criteria
The following qualifications will be considered an advantage:
- Good knowledge of mathematical optimization (e.g., mixed-integer linear programming, stochastic programming, meta-heuristics)
- Knowledge of machine learning and/or AI methods
- Experience with algorithm development
- Proficiency in at least one programming language, e.g, Python, Julia, C++, or similar
- Interest in applications in transport, logistics, or operations planning
Applicants in the final phase of their master’s studies are encouraged to apply
Personal characteristics
We are looking for a candidate who:
- Is intellectually curious and motivated to conduct high-quality research
- Works independently and in a structured manner
- Has strong communication and collaboration skills
- Thrives in interdisciplinary research environments
- Is interested in developing research with practical relevance and societal impact
Emphasis will be placed on scientific quality, research potential, and personal suitability.
We offer
- An exciting and international academic environment with opportunities for competence development
- Opportunities to collaborate with leading researchers in optimization and AI
- Close interaction with industry partners and public sector stakeholders
- Participation in a national centre of excellence on AI for decision making
- Opportunities for research stays at international universities
- An open and inclusive workplace with engaged colleagues
- Favorable terms in the Norwegian Public Service Pension Fund
- Employee benefits
- Good loan, insurance, and pension schemes in the Norwegian Public Service Pension Fund
- Norwegian language training at a basic level (A2)
- Working at NTNU
Information about working and living in Norway can be found at the following link: https://www.workinnorway.no/en/Home
Diversity
Diversity is a strength, and at NTNU we aim to be an employer that reflects the diversity in society and that makes use of the potential of the population's collective skills. Our vision is Knowledge for a better world and our values are creative, critical, constructive and respectful. We believe that an organization that is equal, diverse and gender-balanced is essential for us to achieve our goals.
We strive to attract employees with different skills, life experiences and perspectives to contribute to even better problem solving of our societal mission in research and education.
If you think this position is relevant and interesting, we encourage you to apply, regardless of gender, functional ability and cultural background, or whether you have been out of work for a period of time.
Salary and conditions
PhD candidates are remunerated in code 1017, currently NOK 550.800,- per year before tax. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
The period of employment is 3 years without required teaching duties.
Appointment requires admission to the PhD programme at the Faculty of Economics and Management at NTNU.
Trondheim is the workplace. For necessary professional and social interaction, it is a prerequisite that you are physically present and available to the institution on a daily basis.
The appointment is carried out in accordance with the principles of the State Employees Act, and Export control (legislation that regulates the export of knowledge, technology and services). Candidates who, after assessment of the application and attachments, are considered to be in conflict with the criteria in the latter act, will not be able to be employed.
Any statutory leave will be added to the employment period.
As an employee at NTNU, it is important to stay updated on professional and organizational changes and adapt to these.
About the application
Please note that the application will only be assessed based on the information we have at the application deadline. Therefore, ensure that your application clearly demonstrates how your skills and experiences meet the criteria described above.
The application must contain the following:
- Motivation letter – The motivation letter must clearly state how the candidate meets the qualification requirements.
- Research plan (maximum one page) – Applicants should provide a brief research plan describing how they would approach one or more of the research questions outlined in the description of the position. The plan should reflect the applicant’s research interests and provide an outline of how they envision contributing to the project objectives.
- CV, diplomas, and certificates
- Scientific works, including the master thesis.
- Names and contact information of three potential references
NTNU recognizes a wide range of academic contributions and has committed itself to
The San Francisco Declaration on Research Assessment and
CoARA (responsible assessment of research and recognition of a greater breadth of academic contributions in accordance with NTNU's social mission).
Incomplete applications will not be considered.
General information
A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you wish to be exempt from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation. You will be notified if the exemption is not granted.
If you think this position looks interesting and in line with your qualifications, you are welcome to apply.
Questions about the position can be directed to Associate Professor Steffen Jaap Skotvoll Bakker (steffen.bakker@ntnu.no), Professor Magnus Stålhane (magnus.staalhane@ntnu.no), and Research Manager Torkel Haufmann (torkel.haufmann@sintef.no).
If you have any questions regarding the employment process, please contact HR Advisor Hilde Selli Egelie at hilde.s.egelie@ntnu.no.
Application deadline: 16.08.2026
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For practical information about working at NTNU, please visit this webpage.
The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the tech capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.