Implementing AI in gut health diagnostics and monitoring in poultry (ref. BAP-2023-209):

The primary location for the PhD student will be at PoulPharm. Poulpharm is a fast-growing veterinary diagnostic lab and a contract research organization, executing clinical animal studies for poultry and swine. The lab produces autogenous vaccines and runs parasitological, bacteriological, serological and virological diagnostics.

Recent extensive expansion of the facilities supports the upcoming demand by the sector. Being key expert in in-depth diagnostic knowledge, PoulPharm can proudly position itself as leader within the poultry diagnostic labs. The PhD student will be coached by experts from the research group PSI/MIC (MIC = Medical Image Computing) in the Department of Electrical Engineering (ESAT).

MIC is since long active in the field of (bio)medical imaging research. One of its main strengths is its unique setting in the Medical Imaging Research Center (MIRC), an interdisciplinary research center with core location in the University Hospital Gasthuisberg. MIC aims to be a European top research group, reflected by an outstanding publication record and an extensive valorization with respect to international collaboration, acquired patents, spin-off creation and visibility in general.


The HANPEI (Higher Accuracy and Novel Parameter Exploratory Investigations in poultry gut health) project consists of three research parts and one part development. Within the researchpart of the project, the existing methods for gut health monitoring anddiagnostics will be investigated in three different domains: gross pathology, histopathology,and parasitological examination.

 Coccidiosis, bacterial enteritis, and necroticenteritis are the three main enteric diseases impacting gut health and are leadingto massive economic losses and compromised animal welfare worldwide. The aim isto lift the currently outdated and highly subjective methods to a new state ofthe art by using artificial intelligence to increase objectivity and accuracyof results.

In thefinal stage of the project, findings from research parts will be translated anddeployed for in field application. The goal will be to develop an applicationthat is highly practical for in field usage, where poultry farmers from allover the world can input data and get automatically generated advice.

The focusof the PhD-student will be on the technological side, which consists of twomajor parts. First, you will be responsible for developing a robust acquisitionprocess that will be used to create a dataset of high-quality images for grosslesion scoring. This includes the hardware setup (camera, lighting, referenceboards, etc.) and post-processing algorithms (contrast enhancement, backgroundsegmentation, etc.) to minimize variation that is not caused by pathology.

Thisdataset will then be labelled by trained experts. Second, you will develop andimplement a convolutional neural network to automatically score images from thisdataset, taking into account the difficulties of the data at hand (highresolution images, missing or inconsistent data labels, etc.). You will workclosely with a second PhD student, whose focus will be on the biologicalrelevance of the findings and relate these to disease pathogenesis, animalphysiology etc. 


  • You old a master in bio-engineering, bio-informatics or master of artificial intelligence.
  • EU or international candidates will be accepted.
  • You have good English written and oral communication skills.
  • You have an interest in the veterinary sciences and poultry production.
  • You have a European driving license (category B)
  • You have a specific interest in research valorisation and preclinical studies


A full-time position for four years during which you have the chance to work with experts from the fields of medical imaging, digital pathology, and veterinary sciences.


For more information please contact Prof. dr. Peter Claes (, Prof.dr. Gunther Antonissen (,  or dr. Philip Joris ( You can apply for this job no later than July 03, 2023 via the online application tool

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