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Ben Aernouts

Professor at KU Leuven

KU Leuven

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Belgium

Has open position

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Research Interests

Animal Science

80%

Food Science

60%

Ruminant Physiology

50%

Livestock Management

50%

Lactation Physiology

30%

Spectroscopy

30%

Dairy Science

30%

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Positions1

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Ben Aernouts

University Name
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KU Leuven

IoT in Agriculture: Novel Sensor Technology for Online Milk Quality and Cow Health Monitoring (PhD)

The Livestock Technology research team at KU Leuven, led by Professor Ben Aernouts, invites applications for a PhD position focused on the development of novel sensor technology for online milk quality and cow health and welfare monitoring. The project addresses the growing need for sustainable dairy farming by integrating automation and advanced health monitoring systems for individual animals. The research lab is based at KU Leuven's Geel campus, situated in a rural environment and collaborating closely with research farms, industry partners, and the livestock sector. Dairy production is a significant segment of global agriculture, and modern practices have increased milk yield per cow through genetic selection and improved management. However, this intensification has also led to production-related disorders in dairy cows. The project aims to leverage the metabolic information contained in milk to monitor cow health efficiently. Current online measurements in dairy farming include milk production, conductivity, and color, but these parameters are influenced by various factors beyond health status. Therefore, the research seeks to develop monitoring parameters with a more direct link to cow health, focusing on milk components such as fat, protein, and lactose, which reflect feed uptake, metabolic status, and udder health. The core of the project involves designing and building an optical sensor prototype using miniature spectrometers to measure milk quality. This technology will be implemented in automatic milking systems, enabling monitoring at the level of individual mammary glands. By comparing quarters within the udder, systemic effects can be eliminated, supporting a high-performance warning system for mastitis detection. The robustness of the sensor will be enhanced through multivariate calibration strategies and machine learning approaches. Sensor measurement variation will be analyzed in relation to cow health, combined with advanced data-processing techniques to develop a robust early-warning system. The ideal candidate will have a strong interest in sensor technology, data processing, and scientific research, and will be eager to work at the intersection of bioscience, engineering, and precision farming. Applicants must hold an MSc degree (with minimal distinction) in biosciences, bioscience-engineering, engineering (technology), or equivalent, obtained within the last 3 years from a university in the European Economic Area (EEA). Experience with scientific data-processing software (such as Matlab, Python, R, C, Labview) and statistics/chemometrics is advantageous. Good oral and written communication skills in English are required, along with a creative, critical, analytical, and innovative mindset. The position is not open to candidates without the specified MSc degree or those who obtained their degree outside the EEA. KU Leuven offers a full-time PhD position with a competitive salary for 4 years, preferably starting on September 1, 2026. The successful candidate will join a young, dynamic, and multidisciplinary team, receive comprehensive scientific training, and benefit from excellent education and learning opportunities at a top-ranked university. Collaboration with the research center for dairy production “Hooibeekhoeve” and the milking technology industry is integral to the project. Opportunities for participation in national and international meetings, network building, and skill development are provided. KU Leuven is committed to fostering an inclusive, respectful, and socially safe environment, embracing diversity as an asset and ensuring equal opportunity for all. For further information, contact Prof. Ben Aernouts at [email protected]. Applications should be submitted via the KU Leuven jobsite application link. Please ensure you meet the eligibility criteria before applying.

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Articles18

Collaborators5

Veerle Fievez

Professor at Ghent University

Ghent University

BELGIUM

Tuomo Juhani Kokkonen

University of Helsinki

FINLAND

Wouter Saeys

Professor Dr. Ir. at KU Leuven

KU Leuven

BELGIUM

Matti Pastell

Associate Professor

Natural Resources Institute Finland (Luke)

FINLAND

Giulio Cozzi

Full Professor

University of Padova

ITALY