Postdoc in Computer Vision and Smart Sensing for Sustainable Aluminium Recycling

Leverage computer vision, smart sensing, and AI approaches to advance aluminium recycling and accelerate the transition to a circular economy.

Job description

Aluminium is one of the world's most widely used metals, and its recycling plays a vital role in sustainable metallurgy and a circular economy. However, current aluminium recycling processes face significant challenges, particularly in recovering and sorting aluminium scraps from complex and heterogeneous waste streams. High-quality recycling increasingly depends on advanced sensing technologies that can accurately characterise scrap properties and identify alloy types, enabling more efficient downstream metallurgical processing and improved metal circularity.

Over recent decades, numerous sensing technologies have been developed for metal scrap characterization. Yet, robust and cost-effective solutions suitable for industrial deployment remain limited. Next-generation recycling systems will combine multiple sensing techniques (e.g., optical sensing, spectroscopy, and electromagnetic sensing) with artificial intelligence (AI) to robustly deliver high-quality recycled aluminium for promoting circularity.

The Engineering Structures (ES) Department at TU Delft is seeking a motivated Postdoctoral Researcher to advance smart sensing and AI technologies for sustainable aluminium recycling as part of the Horizon Europe CLEANMAT (Smart Clean Aluminium Material Processing) project. CLEANMAT brings together seventeen partners from eight countries, spanning universities, research and technology organisations, industrial companies, SMEs and industrial associations. The project aims to establish a low-emission, end-to-end pathway for converting challenging scrap streams into high-performance aluminium alloys. CLEANMAT — About the Horizon Europe Project on Clean Aluminium Material Processing

As a postdoctoral researcher, your primary responsibilities will be:

• Develop machine learning and deep learning models, with a strong focus on computer vision, for the characterisation and classification of aluminium scraps and contaminants.

• Design and validate algorithms for multi-sensor data interpretation and sensor fusion.

• Conduct laboratory experiments on scrap characterisation and sorting.

• Collaborate closely with TU Delft researchers and CLEANMAT consortium partners through regular meetings and joint activities.

• Prepare project deliverables, technical reports, and reputable journal publications.

Your host group is the Section of Resources & Recycling (R&R) at TU Delft. Research in the R&R group is renowned for translating scientific research into industrial reality, resulting in about half a dozen spin-out companies to date. As a postdoc researcher in our group, you will have access to advanced sensing and computational facilities at TU Delft and collaborate with leading European universities, research institutes, and industrial partners involved in the CLEANMAT project across Europe. The role offers opportunities to contribute to innovation development, high-impact publications, and the dissemination of results across Europe.

The Department of Engineering Structures focuses on the development of resilient, smart and sustainable structures and infrastructures. Our aim is to meet societal demands in transportation, the energy transition and sustainable reuse. Research themes include dynamics of structures, mechanics of materials related to e.g., climate change, modelling and design of railway systems, multi-scale modelling of pavement materials and structures, reuse of materials, structures and parts of structures, assessment methods for structures, smart monitoring techniques, design methods, replacement and renovation of civil infrastructure and development of new materials and maintenance techniques. Our unique Macro Mechanics Laboratory facilities support full-scale testing, monitoring and modelling of structures to facilitate implementation of innovations. The department delivers both groundbreaking research and world-class education for undergraduate and graduate students. As a team, we represent different backgrounds, skills and views. We foster an inclusive culture, as our combined identities, attitudes and ambitions widen our perspective and make up our strengths.

Job requirements

• A PhD degree in Civil, Mechanical, Automation/Electrical Engineering, Applied Mathematics/Mechanics, Computer Science or related areas.

• Demonstrated experience in one or more of the following areas (1) AI (particularly computer vision), (2) machine learning for data analysis, (3) sensor technologies (e.g., electromagnetic sensors), (4) design and integration of mechanical/electrical devices; and an interest in actively developing the relevant techniques needed for this project.

• Ability to work both independently and collaboratively as part of a multidisciplinary research team, and to adapt to evolving project requirements and priorities.

• Strong skills in data analysis, image processing, and programming (e.g., Python/C++).

• Demonstrated experience in publishing scientific journal papers.

• Fluent in English (oral and written).

TU Delft (Delft University of Technology)

Working at TU Delft means contributing to solutions that really make a difference.

For over 180 years, we have been training engineers who make an impact worldwide in companies, government bodies, or as entrepreneurs. Our alumni turn knowledge into concrete solutions for the challenges of today and tomorrow. These challenges are changing rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future.

At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional. Working at TU Delft means join an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.

Faculty of Civil Engineering and Geosciences

The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource availability, urbanisation and clean water. Our research projects are conducted in close cooperation with a wide range of research institutions. CEG is convinced of the importance of open science and supports its scientists in integrating open science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.

Click  here  to go to the website of the Faculty of Civil Engineering & Geosciences.

Conditions of employment

• Duration of contract is 2 years. Temporary.

• A job of 36-40 hours per week.

• Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.

• An excellent pension scheme via the ABP.

• The possibility to compile an individual employment package every year.

• Discount with health insurers on supplemental packages.

• Flexible working week.

• Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.

• Plenty of opportunities for education, training and courses.

• Partially paid parental leave

• Attention for working healthy and energetically with the vitality program.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service , offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

Additional information

For more information about this position, please contact Dr. Yongli Wu e-mail: Y.Wu-7@tudelft.nl or Dr. Francesco Di Maio, phone: +31 (0)15-2788148, e-mail: f.dimaio@tudelft.nl .

Application procedure

Are you interested in this vacancy? Please apply no later than 3 November 2026 via the application button and upload the following documents:

• CV.

• Cover/motivation letter explaining your interest and your qualifications for this position, a proposal on how you would approach the described problem and how your skills match the requirements.

• MSc + PhD degree.

• 300 words abstract of your MSc and PhD thesis.

• Publication list.

• Two selected publications.

• Applicants selected for an interview will be asked to provide contact information of at least 2 references.

Please note

If your MSc and PhD diploma and transcript are not in Dutch, English, French or German and you will be the selected candidate, the TU Delft will ask you to deliver a certified translation in case you will be appointed.

For information about the application procedure, please contact our secretariat: Secr-ES-CiTG@tudelft.nl .

Please note

• You can apply online. We will not process applications sent by email and/or post .

• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security.

• Please do not contact us for unsolicited services.