Postdoctoral Fellowship (11) at Eindhoven University of Technology, Netherlands

Logistics activities are major contributing factors to the construction sector’s emissions. While synchromodal networks (combining road transport with alternative modes of transport) have shown significant benefits for cost and emission reduction in long-haul transport, they have not seen sufficient uptake in the construction industry where the national borders usually confine the flows. The high weight and volume that characterize construction and demolition cargo make water transportation an ideal candidate for reducing emissions.

The DINALOG project “SYNERCIZE” (Synchromodal Transport Networks for a Construction Industry toward Zero Emissions) fosters long-term sustainable modal shift toward zero-emission waterways by (i) developing digital tools, (ii) optimizing and coordinating the day-to-day operations, (iii) designing networks which easily adapt to changing demand, and (iv) developing business models to support this shift. At TU/e, we are working on the optimization and coordination of operations as well as the network design. We thus invite applications for a PostDoc who is interested in working at the intersection of research and practice in collaboration with municipalities as well as construction companies, who like to further the state-of-the-art in decision-making algorithms for construction logistics, and who is eager to work toward a zero-emission construction industry.

The PostDoc will utilize and develop various methodologies from operations research and operations management, including combinatorial optimization, game theory, (deep) reinforcement learning, , and simulation. Possible topics include:

• Upscaling of inland waterway networks to meet geographically fluctuating demand
• Incentive mechanisms to drive modal shift towards waterways (such as hub locations, schedules, etc which make modal shift easier)
• Pricing schemes on arc/node level to foster modal shift

Healthcare is undergoing rapid transformation, driven by rising chronic disease, workforce shortages, and the urgent need for more efficient, patient-centred models of care. Remote Patient Monitoring (RPM) has become a cornerstone of hybrid care, enabling follow-up outside the hospital while supporting quality, safety, and continuity of care. Heart failure – affecting around 240,000 people in the Netherlands – is one of the most common and fastest-growing chronic conditions to address. Yet large-scale, sustainable RPM remains limited, in large part because of the underlying health-IT infrastructure: centralised data integration approaches that copy, transform, and maintain data in multiple places, creating rigidity, high maintenance costs, limited scalability, and strong vendor dependencies. In response, a paradigm shift is emerging – data interaction – in which data remains in its source systems but becomes available in real time, contextually, and on demand to authorised users and applications. This Postdoc position offers the resources and collaboration to design, document, and further develop methodological insights around data interaction for cross-institutional, hybrid care, with a direct, real-world impact on the heart failure care pathway.

Máxima Medisch Centrum (MMC) and Catharina Ziekenhuis Eindhoven (CZE) already collaborate closely on RPM for heart failure within a regional ecosystem committed to innovation in digital and hybrid care, and a basic data-interaction system has already been realized. As Postdoc, you will lead the design of a unified, cross-institutional heart failure care pathway, develop a system-independent, care-process-driven data definition, and guide the implementation and evaluation of data interaction in daily clinical practice. You will also help shape the business and governance models that allow multiple MedTech vendors (LUSCII, BeterDichtbij, AIKON, Philips) to connect to the data-interaction layer, working towards a transferable foundation that can be scaled to other care pathways. A concrete goal for this Postdoc is to set up an effective design research agenda spanning clinical, technical, implementation, and business perspectives, in close cooperation with an Engineering Doctorate candidate and the clinical, IT, and vendor teams. Next to that, the Postdoc position will be connected to the Eindhoven MedTech Innovation Center (eMTIC).

The position is offered within the Industrial Design Department, Computational Design Systems cluster. Research at the Industrial Design department investigates the everyday interactions between people and the highly interconnected technology that surrounds them. We measure, model, and design for the user experience as individuals engage with social-technological networks — at home, at work, in transit, and at leisure — and create innovations that impact systemic structures and groups of people, addressing large-scale issues such as health, mobility, and sustainability through iterative, circular research-through-design with strategic stakeholder alliances.

This project will be executed together with company Exergy within the EKKO Circular Plastics project. The PD researcher will develop and validate an AI-enhanced, solvent-based recycling process for complex plastic waste streams such as multilayer packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process adaptive and scalable. The research effort will be directed towards the selective recovery in high yield of high-value polymers (e.g., PET, PS, PC, ABS) at high purity, while minimizing solvent consumption and energy demand. The research activities will include understanding of performance profile of recycled polymers by means of various chemical, structural, rheological and mechanical characterization techniques.

The PD research will be carried out under the supervision of Prof. Željko Tomović in the Polymer Performance Materials group in the Department of Chemical Engineering and Chemistry at the TU/e, which is also the part of the interdisciplinary Institute for Complex Molecular Systems (ICMS), in which all polymer-related research groups at the TU/e participate. A description of the group can be found here: www.tue.nl/en/research/research-groups/polymer-performance-materials.

The TU/e offers academic education that is driven by fundamental and applied research. We combine scientific curiosity with a hands-on mentality. Our educational philosophy is based on personal attention and room for individual ambitions and talents. Our research meets the highest international standards of quality. We push the limits of science, which puts us at the forefront of rapidly emerging areas of research.

The successful candidate will be in charge of developing the sensor technology, in collaboration with a PhD student and another postdoc. This includes the design of the photonic chip, the development of a suitable microfabrication process, the testing of fabricated devices and of their application. The project will be carried out under the supervision of prof. dr. A. Fiore, Dep. Applied Physics and Science Education, and carried out in collaboration with external partners. The postdoctoral appointment will initially be for a period of one year, with the possibility of extension for a second year. The Eindhoven region and its PhotonDelta ecosystem offer ample opportunities for developing an applied R&D career in photonics, within large companies or fast-growing spin-offs.

The GUIDE-ME project pursues the following three interconnected objectives:

• Building on existing approaches, develop and evaluate a set of metrics for assessing the impact of open research software.
• Develop actionable guidelines for sharing open research software. This includes analyzing existing open software sharing practices, distilling them into cross-domain best practices, and aligning them with the aforementioned metrics.
• Design and evaluate a training program to disseminate the guidelines and metrics to researchers across disciplines.

Throughout the project, the postdoc will work in close collaboration with the project team and external partners, including the Netherlands eScience Center. The project will be supervised by Dr. Alexander Nolte (TU/e, project lead) and Dr. Jacob Krüger (TU/e), with additional support from Dr. Slinger Jansen (Utrecht University), Dr. Louise Bezuidenhout (Leiden University), and Dr. Carlos Martinez-Ortiz (Netherlands eScience Center).

The position offers an excellent opportunity to develop your own research profile around the project’s themes, publish and present your work at international conferences, develop a professional network within the Dutch and international open science community, and gain experience in organizing workshops and collaborative research events.

The GUIDE-ME project pursues the following three interconnected objectives:

• Building on existing approaches, develop and evaluate a set of metrics for assessing the impact of open research software.
• Develop actionable guidelines for sharing open research software. This includes analyzing existing open software sharing practices, distilling them into cross-domain best practices, and aligning them with the aforementioned metrics.
• Design and evaluate a training program to disseminate the guidelines and metrics to researchers across disciplines.

Throughout the project, the postdoc will work in close collaboration with the project team and external partners, including the Netherlands eScience Center. The project will be supervised by Dr. Alexander Nolte (TU/e, project lead) and Dr. Jacob Krüger (TU/e), with additional support from Dr. Slinger Jansen (Utrecht University), Dr. Louise Bezuidenhout (Leiden University), and Dr. Carlos Martinez-Ortiz (Netherlands eScience Center).

The position offers an excellent opportunity to develop your own research profile around the project’s themes, publish and present your work at international conferences, develop a professional network within the Dutch and international open science community, and gain experience in organizing workshops and collaborative research events.

As offshore renewable energy rapidly expands, a key scientific challenge is to understand how wind farm-induced changes in currents, turbulence, and stratification affect the transport and survival of ichthyoplankton (fish eggs and larvae). These early life stages determine future fish populations, yet their sensitivity to physical changes remains poorly understood.

In this position, you will tackle this challenge by combining fluid dynamics, numerical modelling, and marine ecology to quantify how offshore wind farms alter larval transport pathways and ecosystem connectivity. Your work will contribute directly to sustainable offshore energy development by improving our ability to predict ecological impacts and supporting evidence-based marine spatial planning. In doing so, you will help balance the transition to renewable energy with the protection of marine biodiversity and fisheries.

You will contribute to NO-REGRETS (North Sea Renewable Energy: Gaining the Required Ecological Knowledge for the Transition) is a six-year (2025–2031) interdisciplinary project funded by NWO. It investigates the ecological and economic impacts of large-scale offshore wind farm expansion in the North Sea under climate change. Bringing together universities, research institutes, and stakeholders, the programme studies effects on physical processes, marine ecosystems, and fisheries, and develops tools to support sustainable decision-making and marine spatial planning. You will work at Fluid & Flows group at TU/e, an internationally recognized group studying complex transport phenomena in environmental and engineering systems, and you will work closely together with researchers across disciplines including at NIOZ (The Netherlands Institute for Sea Research) and Deltares, benefiting from a collaborative and supportive environment.

Are you passionate about human-AI teamwork? A significant, highly complex class of AI applications are sequential decision-making problems, where a sequence of actions needs to be planned and taken to achieve a desired goal. Examples of such settings include routing problems, in which the navigation from a source to a destination consists of a sequence of steps; or the control of manufacturing processes in real time, which consist of a variable sequence of operations. Unfortunately, users often do not understand current AI decision-making very well, leading to decreased trust and acceptance. Additionally, current AI systems do not understand users very well, making their decisions blind to the users’ actual needs and preferences. This hinders human-AI collaboration.

The European PEER project is an interdisciplinary project between artificial intelligence, social sciences, and societal partners, that aims at enabling deeper and more meaningful interaction and collaboration of AIs and users. Its overall objective is to build interactive and understandable sequential decision-making AI systems that empower end-users by providing them with flexible, personalized solutions adapted to their requirements and capabilities. This goes far beyond the capabilities of current approaches for example in the field of Explainable AI (XAI) or Explainable Reinforcement Learning (XRL).

We offer you the exciting opportunity to join this Europe-wide project (involving academia, industry, and non-profit partners) as a Postdoc. Your role will be to develop novel human-centric AI algorithms and techniques for reinforcement learning and planning settings, to enable interactions that allow humans to better understand and trust their AI assistants, and that allow AI systems to better understand and support their human users. We aim for users and AI systems to explore possible plans and solutions together; for more fluid mutual learning and reasoning, and a more helpful conversation between humans and AI.

Continuous wave radar with frequency modulation (FMCW radar) has gained traction in automotive safety systems, such as adaptive cruise control and collision avoidance, and it is now a core sensor in self-driving cars. One of the key conditions for the proper functioning of an FMCW radar is guaranteeing sufficient isolation between the transmitting and receiving antenna. An accurate assessment of such isolation is thus of paramount importance in the radar design.

Reverberation chambers are a well-established testing approach both in the field of electromagnetic compatibility as well as for measuring integral radiation quantities of stand-alone antennas (antenna efficiency) and wireless devices (Total Radiated Power, Total Isotropic Sensitivity).

In addition to that, research on antenna radiation pattern measurements in reverberation chambers has started to draw attention. Most methods are based on the property that the line-of-sight component is constantly present in each of the measurements performed on the AUT, and that unwanted scattered components can be averaged out by randomizing the electromagnetic environment in a controllable manner.

Instead, measuring isolation between two arrays, or coupling between measurements inside an array is a completely unexplored area, which will require additional fundamental research.

Your objective in this research project is thus to develop a methodology for accurate and reliable measurement of coupling between antennas in reverberation chambers.

In this project you will cooperate with Robin Radar, a manufacturer of FMCW radar and potential end-user of the results, and with Antennex, a Dutch SME that develops reverberation chambers. Antennex has made fundamental extensions to measurement capabilities in reverberation chambers, for instance, noise figure, FMCW chirp quality and radiation pattern measurements. Enabling isolation measurements would offer a new use case for reverberation chambers, which might be more cost effective compared to the existing anechoic chamber approach.