PhD position on ‘Laser scatter imaging for plant stress detection in greenhouse crops'

Karlstad University; Leuven; Sur place; EUR 30 000 - 35 000; Plein temps

Avantages offerts par ce poste

State-of-the-art research infrastructure

Excellent guidance from a dynamic team

High level scientific training

Résumé du poste

Karlstad University in Leuven invites applications for a PhD position focusing on ‘Laser scatter imaging for plant stress detection in greenhouse crops.’ This role involves developing innovative sensor technologies for greenhouse crop management through early detection of plant stress.

The successful candidate will contribute to a multidisciplinary team, engage in state-of-the-art research, and have a hands-on role in designing a sensor prototype. A full-time position is offered, initially for 1 year, with potential extension up to 4 years based on evaluations.

Qualifications

• Strong interest in/affinity with greenhouse farming and plant stress detection.
• Analytical mind for modelling light interaction with plant tissues.
• Independent worker that shows initiative and respects deadlines.

Responsabilités

• Develop a camera-based multispectral laser scattering imaging setup.
• Analyse scatter images to extract scattering and absorption properties.
• Test and validate the prototype sensor on plants.

Connaissances

Interest in greenhouse farming

Analytical skills

Proficiency in Matlab/Python

Hands-on attitude

Fluency in English

Formation

Master's degree or equivalent

Outils

Labview

Description du poste

PhD position on ‘Laser scatter imaging for plant stress detection in greenhouse crops'

KU Leuven is an autonomous university. It was founded in 1425. It was born of and has grown within the Catholic tradition.

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 focuses 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.

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 optimise the use of energy, water and nutrients, and where possible decrease the amount of labour needed. To transition towards optimised autonomous cultivation in greenhouses, one of the important pillars is the development of new crop monitoring sensors that allow optimised 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 biochemic 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 analysing 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 optimised for measuring on plant leaves
• Analyse 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 optimisation of greenhouse operational practice.

• 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)

Application

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: [e-mail] or Dr. Annelies Postelmans, mail: [e-mail].

KU Leuven strives for an inclusive, respectful and socially safe environment. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential for an ambitious research and educational environment. In our commitment to equal opportunity, we recognise the consequences of historical inequalities. We do not accept any form of discrimination based on, but not limited to, gender identity and expression, sexual orientation, age, ethnic or national background, skin colour, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or support offered, we are happy to assist you at this email address.

Job details

Title: PhD position on ‘Laser scatter imaging for plant stress detection in greenhouse crops'

Closing date: 2026-08-18 (Europe/Brussels)