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.
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.
About the department
The HBE cluster is dedicated to encouraging a supportive and inclusive working culture. Our aim is that all job applicants are given equal opportunities. When we select candidates for employment, it will be on the basis of their competence and ability. To support workforce diversity, we are open to offering flexible working conditions on an individual basis to support work-life balance, which may include a contract of employment, working hours and location, or childcare arrangements.
The High Business Entrepreneurship corporate video can be watched via this link.
About the organisation
At the Faculty of Behavioural, Management and Social Sciences (BMS), we unite the worlds of people and technology to address today’s complex societal challenges. We are passionate about understanding human behaviour, fostering responsible innovation, and designing solutions that create societal value. Our educational programmes span disciplines such as Psychology, Business Administration, Public Administration, Communication Sciences, Philosophy, Educational Sciences, and Health Sciences. Through our bachelor’s and master’s degrees, Professional Learning & Development programmes, and interdisciplinary research themes – including Emerging Technologies & Societal Transformations, Resilience, Smart Industry, Learning, and Health – we empower students and researchers to make a positive societal impact.
At BMS, we combine critical thinking with practical action. From advancing sustainable mobility with innovations like the world’s most efficient hydrogen car to shaping policies that promote digital inclusion, our work contributes to a healthier, fairer, and more sustainable future. Whether it’s exploring how technology influences human behaviour or leveraging data and innovation to transform industries and communities, we ensure that technology serves people – and not the other way around.
As an employer, BMS offers a vibrant, inclusive, and entrepreneurial environment where you can thrive personally and professionally. Join us and become part of a forward-thinking community that equips you to shape the future – for yourself and society. With us, you will become part of a leading technical university with increasing, positive social impact.
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