The MeBioS research unit performs groundbreaking research on innovative sensor technologies and the associated data analysis methods to understand and control the quality of (mainly) biological products and processes, as well as applications in precision agriculture. Within its Biophotonics group, sensor research focusses on optical systems in different parts of the electromagnetic spectrum, including Vis/NIR spectroscopy, THz spectroscopy and imaging, hyperspectral imaging, thermography and smart cameras. The associated data research involves the optimal design of experiments, chemometrics, process monitoring and control, as well as artificial intelligence and deep learning.
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Project
Protected cultivation of vegetables in greenhouses is an agricultural system characterized by a high yield per m². To achieve this, it requires intensive inputs in terms of labor, energy, production means and capital. Therefore, considerable efforts are being made to optimize the use of energy, water and nutrients, and where possible decrease the amount of labor needed. To transition towards optimized autonomous cultivation in greenhouses, one of the important pillars is the development of new crop monitoring sensors that allow optimized greenhouse control based on actual crop data.
This research focuses on early detection of plant stress, primarily in tomato plants, by means of the optical technique laser scatter imaging. Plants react to (a)biotic stressors by adapting their biochemical composition (e.g. chlorosis) and microstructure (e.g. cell wall thickness, porosity of leaf tissue). These changes are often subtle and only detected by the human eye in a more advanced stage. By combining camera vision with specific illumination patterns, this project aims at an early detection of stress responses in plant leaves, allowing a timely adjustment of the greenhouse control.
To this end, laser scatter images of plant leaves will be captured at different wavelengths. By analyzing the glow area around the illumination pattern, the effects of light scattering and absorption, respectively related to microstructure and pigmentation, will be untangled. To come to a functional, multispectral prototype of this scatter imaging sensor, we will
- Develop a camera-based multispectral laser scattering imaging setup with wavelengths and illumination pattern optimized for measuring on plant leaves
- Analyze scatter images to extract scattering and absorption properties and link these to plant microstructure, pigment concentration and water status
- Test and validate the prototype sensor on healthy and stressed plants in lab and greenhouse conditions
Profile
We are looking for a highly motivated PhD candidate to join our team in this mission to contribute to the optimization of greenhouse operational practice. Do you hold a MSc degree in Engineering (bioscience, electrical, optical) or in Science (physics, photonics) and do you match with the following requirements? Then you may be the colleague we are looking for!
- Strong interest in/affinity with greenhouse farming and plant stress detection are a plus
- Analytical mind for modelling the interaction between light and plant tissues, processing scatter images and translating the results to plant stress status information
- Hands-on attitude to design and build a sensor prototype and develop associated control software
- Programming skills for data processing (Matlab/Python) and developing setup control software (Labview)
- Proactive in communication and reporting, seeking feedback both internally as well as from project partners
- Independent worker that shows initiative, takes ownership of the work, respects agreements and deadlines
- Fluent written and oral communication in English
Offer
- We offer a full-time PhD position for 1 year. After positive evaluation, the contract can be extended up to 4 years.
- Excellent guidance by our young, dynamic and multidisciplinary team
- State of the art research infrastructure.
- A challenging job in a young, dynamic environment.
- High level scientific training at a top-ranked university.
- Being part of a world-class research group.
- Remuneration according to the KU Leuven salary scales (https://www.kuleuven.be/personeel/jobsite/en/phd-info)
Interested?
Candidates are invited to submit their application via the KU Leuven online application tool no later than July 30th, 2026. Please note that applications will be screened on a rolling basis, and suitable candidates may be selected and interviewed before the deadline. Early applications are therefore strongly encouraged. Documents to provide:
- Motivation letter (maximum 1 A4 page), outlining your motivation for the position and how your strengths and background align with the project. Also include your earliest possible start date.
- Curriculum Vitae, including details of your education, current position, relevant work experience (if any), relevant extracurricular activities, and references we may contact.
For more information please contact Prof. dr. ir. Wouter Saeys, mail: [email protected] or Dr. Annelies Postelmans, mail: [email protected].
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