Background
Hasselt University is looking for a new academic staff member within the Faculty of Industrial Engineering. The position is associated with the Institute for Materials Research (imo imomec). Imo-imomec is an interdisciplinary research institute focused on the development of advanced materials and their applications in energy storage, circular materials, quantum technologies and healthcare. The institute combines deep knowledge of physics, chemistry and engineering sciences to provide solutions to global sustainability challenges. Within this framework, there is a strong need to integrate AI and ML as tools for materials research, especially for optimizing processes such as energy storage, material efficiency and device reliability.
Education task
You will initially focus mainly on research, with a limited teaching role in the undergraduate and graduate programmes within engineering technology or the undergraduate and graduate programmes within sciences (physics, chemistry) at UHasselt. You will assume the coordinating role of at least one course unit.
Research mission
You will contribute to advancing the integration of Artificial Intelligence (AI) and Machine Learning (ML) within imo-imomec’s materials research. As PI within the institute, you will have the opportunity to choose one of the following key domains in which to apply their expertise, leveraging AI/ML techniques to address fundamental and applied challenges:
- Materials for Energy Storage and Conversion: In this domain, you will use AI/ML techniques to optimise materials for energy storage (such as batteries) and energy conversion systems (such as photovoltaics and power-to-molecules technologies). The candidate may develop data-driven methods for the discovery and synthesis of new materials, modelling battery performance, improving photovoltaic system reliability, and optimising hydrogen production through predictive analytics. This research will contribute to the development of more sustainable and efficient energy storage systems, with a focus on renewable energy and energy efficiency.
- Circular Materials and Sustainability: AI/ML techniques will play a key role in developing circular polymers, sustainable materials, and recycling processes. You will apply AI-driven methods to optimise waste stream conversions, design durable and recyclable biomaterials, and predict structure-property relationships of new environmentally friendly materials. This research area aims to support a circular economy and reduce the environmental footprint of materials by enhancing material reuse and optimising material flows.
- Quantum technologies: You may apply AI/ML techniques to optimise quantum materials and devices, such as those used in quantum sensing, quantum communication, and quantum computing. This research will focus on developing new AI/ML methods to improve the performance and reliability of quantum devices and to discover new materials with enhanced quantum properties. The outcomes of this research could drive breakthroughs in quantum technologies for applications like supercomputing and secure communication.
- Advanced healthcare and sensors: In healthcare, materials play a crucial role in the development of diagnostic tools and biomedical devices. You will use AI/ML techniques to optimise the performance of materials used in healthcare applications, such as sensors, smart surfaces, and interfaces. The research will focus on developing predictive models to enhance biomedical devices and create innovative diagnostic technologies. This will contribute to advances in healthcare, particularly in the fields of personalised medicine and diagnostics.
- Device Performance and Reliability: AI/ML can also be used to improve the performance, reliability, and recyclability of devices across various material applications. You will develop AI-driven solutions to address challenges related to device lifespan, predictive maintenance, and high-throughput data analysis to optimise the full lifecycle of materials and devices. This research focuses on enhancing the reliability of materials and devices, extending their economic lifespan, and improving the sustainability of technological systems.
Profile
- You obtained a PhD in a relevant field, such as materials engineering, science, physics, chemistry, or computer science, with a strong specialisation in Artificial Intelligence (AI) or Machine Learning (ML) applications in one of the relevant domains. You have at least 4 years of postdoctoral research experience. (or equivalent)
- Proficiency in developing or applying AI/ML models for material discovery, optimization, and performance prediction. Furthermore, demonstrated expertise in applying AI/ML to one or more domains of the institute imo-imomec.
- You have a proven track record of high-quality publications in internationally recognized journals and presented at known international conferences in the domain. Furthermore, you have experience in leading or contributing to interdisciplinary research projects.
- You have strong interdisciplinary skills to work across both experimental and computational research domains, and experience with handling and analyzing from small to large datasets in a materials science context.
- You have proven experience in supervising PhD students and postdocs and the ability to collaborate with teams across different research disciplines (e.g., chemistry, physics, engineering) within imo-imomec and beyond the institute.
- You have a strong international reputation in AI/ML applications, with active participation in international networks and collaborations and experience in securing competitive research funding at a national or international level.
- You are able to work both independently and in collaboration with others, with a focus on driving innovative solutions to complex materials science challenges.
- You have excellent communication skills, both written and verbal, in English. If you don't speak Dutch, you must be willing to learn it within a reasonable timeframe.
- Dutch is the official administrative language of Hasselt University. If you do not have a sufficient knowledge of Dutch (CEFR level B2) upon your appointment, we expect you to obtain the required level no later than 5 years after being appointed or at the moment of tenure (usually after an internship of 3 years for senior academic staff). We provide tailor-made language training. Coordinating lecturers must have a command of the language of instruction of the program component at CEFR level C1. We provide tailor-made language training.
Offer
We will offer a fulltime appointment as an associate professor or higher, which will lead to tenure. In case of a first appointment as a member of the academic staff, the Board of Directors of the University can decide on a temporary appointment for a period up to 3 years. This will lead to a permanent contract if the Board of Directors favorably assesses the party involved. Upon appointment, you will work as a research professor for the first five years. After favourable evaluation, this period can be extended for another five years.
Selection procedure
You can only apply online up to and including 06 June 2025.
The selection procedure consists of a preselection based on application file, an interview and a test lesson / presentation.
An assessment for the selected candidates is part of the selection procedure.
Further information
Prof. dr. ir. Ronald THOELEN, +32-11-268829, [email protected]
Prof. dr. Marlies VAN BAEL, +32-11-268307, [email protected]
For questions about the selection procedure, please email [email protected].
