PhD Candidate position: Hybrid AI-Optimization for Dynamic and Stochastic Transport Operations

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Video: https://youtu.be/Xt-yHCN5QS0About the positionWe 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 environmentThe 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 projectThe PhD candidate will:

Conduct original scientific research related to the project topicDevelop new algorithms and methods combining AI and optimizationPublish research results in leading international journals and conferencesCollaborate with academic and industry partnersParticipate in aiD centre activities and research meetingsComplete the required coursework as part of the PhD programmeContribute to dissemination and communication of research results
Required selection criteriaApplicants 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 researchComputer scienceArtificial intelligence or machine learningApplied mathematicsEngineering disciplines with strong quantitative and algorithmic contentApplicants 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 criteriaThe 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 methodsExperience with algorithm development Proficiency in at least one programming language, e.g, Python, Julia, C++, or similarInterest in applications in transport, logistics, or operations planningApplicants in the final phase of their master’s studies are encouraged to apply

Personal characteristicsWe are looking for a candidate who:

Is intellectually curious and motivated to conduct high-quality researchWorks independently and in a structured mannerHas strong communication and collaboration skillsThrives in interdisciplinary research environmentsIs interested in developing research with practical relevance and societal impact
Emphasis will be placed on scientific quality, research potential, and personal suitability.

We offerAn exciting and international academic environment with opportunities for competence development Opportunities to collaborate with leading researchers in optimization and AIClose interaction with industry partners and public sector stakeholdersParticipation in a national centre of excellence on AI for decision makingOpportunities for research stays at international universitiesAn open and inclusive workplace  with engaged colleagues Favorable terms in the Norwegian Public Service Pension FundEmployee benefitsGood 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

DiversityDiversity 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 conditionsPhD 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

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