Fully Funded PhD Scholarship: IoT Sensor Technology for Online Milk Quality and Cow Health Monitoring – Belgium
About KU Leuven
Applications are open for a PhD IoT Milk Quality Sensor Belgium position at KU Leuven’s Livestock Technology research group. The project develops an optical sensor prototype using miniature spectrometers for online milk quality and cow health monitoring. KU Leuven is a top-ranked university in Belgium. The research team “Livestock Technology” is led by Prof. Ben Aernouts and develops, implements, and validates innovative sensor technology and data processing algorithms to support animal management in livestock production. The research lab is hosted on the KU Leuven campus in Geel, located in a green and rural environment, in close collaboration with research farms, industry, and the livestock sector.
Scholarship Overview
Project Description
Worldwide, dairy production is an important segment of agricultural production. Over the last 50 years, average milk production per cow has increased enormously, but modern dairy cows are prone to production-related disorders. Regular analysis of produced milk is considered the most efficient way to monitor cow health because milk contains valuable information on the metabolic status of the cow.
In this project, an optical sensor prototype will be designed and built based on miniature spectrometers to measure milk quality. This sensor technology will be implemented in automatic milking systems to monitor milk quality at the level of individual mammary glands (inter-quarter comparison), supporting a high-performance warning system for identifying mastitis. The robustness of the sensor will be evaluated and improved using multivariate calibration strategies and machine learning approaches.
Why This Scholarship Stands Out
This PhD is unique because it sits at the intersection of sensor technology, machine learning, and dairy science. You will design and build an optical sensor prototype using miniature spectrometers – a hands-on engineering challenge. The sensor will be implemented in automatic milking systems to monitor milk quality at the level of individual mammary glands (inter-quarter comparison), enabling early detection of mastitis. The project combines hardware development (sensor design) with data processing (multivariate calibration, machine learning). You will work closely with the research center for dairy production “Hooibeekhoeve” and milking technology industry. For a student interested in precision livestock farming, sensor technology, and data science, this is an opportunity to develop a tool that could directly improve dairy cow welfare and farm efficiency.
Key Responsibilities
- Design and build an optical sensor prototype based on miniature spectrometers to measure milk quality
- Implement sensor technology in automatic milking systems
- Monitor milk quality at the level of individual mammary glands (inter-quarter comparison)
- Evaluate and improve sensor robustness using multivariate calibration strategies and machine learning
- Study variation of sensor measurements in relation to cow health
- Combine measurements with advanced data-processing techniques to obtain a robust early-warning system
Candidate Profile and Eligibility
| Requirement | Details |
|---|---|
| Education | MSc degree (with minimal distinction) in Biosciences, Bioscience-Engineering, Engineering (Technology), or equivalent |
| Recency | Degree obtained in the last 3 years at a university in the European Economic Area (EEA) |
| Mindset | Hands-on engineer with creative, critical, analytical, and innovative mindset |
| Language | Good oral and written communication skills in English |
| Teamwork | Eager to work in multidisciplinary and diverse team |
| Interest | Strong interest in sensor technology, data processing, and scientific research |
| Career Interest | Interest in building a career in sensor technology and data science |
Desirable:
- Experience with scientific data-processing software (Matlab, Python, R, C, Labview, or similar)
- Experience with statistics and chemometrics
- Interest in dairy farming
What They Offer
| Benefit | Details |
|---|---|
| Duration | 4 years (full-time) |
| Start Date | September 1, 2026 (preferred) |
| Location | Geel, Belgium |
| Salary | Competitive salary |
| Research Environment | Young, dynamic, multidisciplinary team |
| Collaboration | Hooibeekhoeve (dairy research centre) + milking technology industry |
| Training | Proper scientific training at top-ranked university, excellent education and learning opportunities |
| Networking | Opportunities to participate in national and international meetings |
My Application Strategy
- Highlight your engineering or bioscience background – MSc in engineering, bioscience-engineering, or equivalent
- Emphasize hands-on experience – Building prototypes, working with sensors, or optical systems
- Show programming and data processing skills – Matlab, Python, R, C, or Labview experience is a plus
- Demonstrate interest in chemometrics or statistics – Multivariate calibration and machine learning are key
- Express interest in dairy farming – Understanding of the application context is valuable
Who Should Apply
This PhD is perfect for a student with an engineering or bioscience background who wants to develop sensor technology for precision livestock farming. If you enjoy hands-on prototyping (building optical sensors), working with data (machine learning, chemometrics), and collaborating with industry partners (milking technology companies, dairy research centres), this project offers training across hardware and software. Candidates from EEA countries who have completed their MSc within the last 3 years are eligible. The ideal candidate is someone who wants to build a career at the intersection of sensor technology and data science.
How to Apply
Apply via the online application tool at KU Leuven.
Application deadline: July 15, 2026
For more information, contact: Prof. dr. Ben Aernouts – ben.aernouts@kuleuven.be
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