EngD or PostDoc Position on Future-Proof, Self-Organizing, Smart Logistics

Postdoc @University of Twente posted 2 days ago

Job Description

We are looking for a highly motivated, enthusiastic, and curious EngD (Engineering Doctorate) or PostDoc researcher to join our Industrial Engineering & Business Information Systems (IEBIS) section at the Faculty of Behavioural, Management and Social Sciences. This position allows you to contribute towards a future-proof logistics system with a special focus on machine learning-based collaborative scheduling, resource sharing, and self-organisation.

The EngD position corresponds to a 2-year post-master design program being part of the program Business Information Technology. For more information on the BIT EngD program, see https://www.utwente.nl/en/education/tgs/interested-in/engd/programmes/.

The PostDoc position is for 1-year.

Background

The logistics sector in the Netherlands is a vital economic pillar, employing over 673,000 people and contributing €65 billion annually. However, the sector faces pressing challenges, such as reducing greenhouse gas emissions, ensuring supply chain resilience amidst disruptions, and overcoming infrastructure and workforce shortages. With freight transport projected to grow by 20% by 2030, these challenges require a shift from isolated logistics operations to collaborative, connected logistics networks. Upcoming policy measures, including kilometre chargers, CO2 caps, the Emissions Trading Scheme, and the Corporate Sustainability Reporting Directive, add urgency to this transition.

A promising framework for addressing these challenges is the Physical Internet (PI), which envisions a transformative shift in logistics systems. The PI concept aims to “do more with less” by enabling the sharing of assets within the freight and transport industries. This involves transitioning from the isolated scheduling of proprietary assets to the collaborative scheduling of shared resources in open, connected logistics networks.

This position is part of TNO’s Early Research Program on Future-Proof Smart Logistics. It aims to contribute to the realisation of the PI concept by developing advanced machine learning-based decentralised decision-making algorithms. These algorithms will enable logistics companies to collaborate effectively and optimise operational scheduling across multi-actor systems, ensuring sustainability and efficiency at both company and system levels.

Research Objectives

The research will address key challenges and explore the following areas:

1. Decentralized Scheduling Algorithms: Design algorithms for operational scheduling and rescheduling of shared assets in connected logistics networks. The research will focus on addressing challenges like efficiency, sustainability, scalability, data sovereignty, and alignment of subsystems.
2. Machine Learning for Collaborative Logistics: Investigate innovative machine learning methodologies, such as federated learning, to enhance decision-making in logistics scheduling. These approaches will be compared to more traditional (deterministic) operations research methods to identify their respective advantages and application scenarios.
3. Integration and Methodological Evaluation: Develop a proof of concept to assess, integrate, and implement decentralised scheduling approaches on real world instances. This will include specifying which methods are most suitable for different logistical challenges, considering constraints like collaboration agreements and data availability.

The research will contribute to creating a roadmap for implementing the PI concept, focusing on practical solutions to make logistics systems self-organising, efficient, and future-proof.

Your profile

We look for a highly motivated, enthusiastic researcher who is driven by curiosity and has/is:

  • Master’s degree (for EngD) or PhD degree (for PostDoc) in Industrial Engineering, Operations research, Computer Science, Econometrics, Transport Engineering, Applied Mathematics, Supply Chain Management, or related discipline;
  • Affinity and/or experience with machine learning and optimisation techniques;
  • Willing to work both at the premises of the University of Twente (Enschede) and TNO (Den Haag);
  • A good team spirit and feel at home in an interdisciplinary environment;
  • Able to do independent research and willing to develop writing and publication skills;
  • Exhibit a strong passion and possess outstanding skills in algorithmic design;
  • Possess good communication skills and an excellent command of English.

Our offer

We encourage high responsibility and independence while collaborating with colleagues, researchers, other university staff and partners. We follow the terms of employment by the Dutch Collective Labour Agreement for Universities (CAO). It also includes:

  • Gross monthly salary of € 2.872 for EngD and depending on the experience a gross monthly salary within a range between € 4.060 and € 5.331 for the PostDoc position;
  • Excellent benefits, including a holiday allowance of 8% of the gross annual salary, an end-of-year bonus of 8.3%, and a solid pension scheme;
  • 29 holidays per year in case of full-time employment;
  • A training programme as part of the Twente Graduate School where you and your supervisors will determine a plan for a suitable education and supervision;
  • A green campus with free access to sports facilities and an international scientific community;
  • A family-friendly institution that offers parental leave (both paid and unpaid);
  • A full status as an employee at the UT, including pension, health care benefits and good secondary conditions, are part of our collective labour agreement CAO-NU for Dutch universities.

Information and application

Are you interested in being part of our team? Please submit your application before 1st of September 2025 and include the following:

  • A cover letter (maximum 2 pages A4), clearly stating whether you apply for the EngD or PostDoc position, and emphasising your specific interest, qualifications, and motivations to apply for this position;
  • A Curriculum Vitae, including a list of all courses attended and grades obtained, and, if applicable, a list of publications and references;
  • An IELTS-test, Internet TOEFL test (TOEFL-iBT), or a Cambridge CAE-C (CPE). Applicants with a non-Dutch qualification and who have not had secondary and tertiary education in English can only be admitted with an IELTS test showing a total band score of at least 6.5, internet. TOEFL test (TOEFL-iBT) showing a score of at least 90, or a Cambridge CAE-C (CPE).

Additional information can be acquired via email from Martijn Mes (m.r.k.mes@utwente.nl). Please do not send applications to this email addresses and mention in the cover letter the vacancy you are applying for.

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