Ghent University · Bioscience Engineering
Machine learning
for the
life sciences
The BioML research group develops principled machine learning methods — with a focus on uncertainty quantification, multi-target prediction, sequence models and probabilistic modelling — and applies them to real problems in biology, agriculture and medicine.
6 researchers working on trustworthy ML
- Publications
- 235+
- Citations
- 11,000+
- Years of research
- 22
- Alumni
- 11
What we do
Research themes
Methodological machine learning research, driven by questions from the life sciences.
Uncertainty quantification & probabilistic models
Knowing what a model does not know — epistemic vs. aleatoric uncertainty, calibration and conformal prediction.
Learn more 02Multi-target prediction
Predicting many related targets at once: multi-label classification, pairwise learning, matrix completion and zero-shot learning.
Learn more 03Applications in the life sciences
Machine learning for -omics data, phenotyping technologies, agriculture, ecology and medicine.
Learn more 04Sequence models & time series analysis
Learning from sequential and spatio-temporal data: from DNA sequences to forecasting and causal inference.
Learn moreThe people
Diverse expertise, shared ambition
Our group brings together researchers with backgrounds in mathematics, computer science, bioscience engineering and bioinformatics. We collaborate closely with partners such as ILVO and leading international machine learning groups.
Latest
News from the lab
Welcome to our new PhD researchers Jitse and Fiebe
Two new PhD researchers join the lab, working on AI for agriculture and on uncertainty-aware multimodal learning.
Read more
Lauren Theunissen defends her PhD thesis
Lauren Theunissen defended her thesis "Addressing Uncertainty in Automatic Cell Type Annotation of Single-Cell Transcriptomics Data".
Read more
Gaetan De Waele defends his PhD thesis
Gaetan De Waele defended his thesis "Self-supervised Transformers for Biological Data Modalities".
Read moreOur research is made possible by support from
Join us
Interested in a PhD or postdoc position?
We are always looking for motivated researchers with a background in machine learning, statistics, mathematics or bioinformatics. Master students can also do their thesis in the lab.