Johan Neyts

KU Leuven is advertising a postdoctoral researcher position in computational biology and machine learning within the ERC AdG project ANTIVIRMAP . The role is based at KU Leuven and is carried out in close collaboration with the Bioinformatics laboratory of Professor Yves Moreau and the broader Leuven.AI environment. The project is aimed at a highly motivated researcher with strong expertise in machine learning modelling and experience working with challenging large-scale datasets . The post specifically highlights skills in deep learning , data fusion , bioinformatics , and practical statistical analysis. Relevant tools and methods include PyTorch or TensorFlow , data cleaning and filtering, kernel methods, Bayesian methods, generative AI, and convolutional neural networks. Applicants with experience in cellular imaging or high-content imaging are especially encouraged, and background in virology , immunology , cheminformatics , or drug discovery is considered a plus. The post also values strong statistical thinking around batch effects, confounders, and experimental design. This is a postdoctoral opening ; no PhD or master’s call is indicated. Funding is tied to the ERC AdG project, but the post does not specify stipend or salary details in the text provided. Interested candidates should use the KU Leuven vacancy page linked in the post and follow the university application instructions there.

The Translational Platform for Virus, Vaccine and Cancer Research (TPVC) at KU Leuven’s Rega Institute offers a PhD position focused on antiviral target discovery for entero- and rhinoviruses. The project is embedded in the Laboratory of Virology and Antiviral Research, led by Prof. Johan Neyts, and involves close supervision within the TPVC team, including Dr. Hendrik Jan Thibaut. Enteroviruses and rhinoviruses are major human pathogens associated with a wide spectrum of disease, from severe neurological complications to asthma and COPD exacerbations. Despite their public health impact, there are currently no approved antiviral treatments. This PhD project aims to accelerate the discovery of antiviral targets by integrating high-content imaging, phenotypic Cell Painting profiling, and AI-driven data analysis to identify host and viral factors essential for infection. The research combines experimental virology with computational and systems-level approaches. The successful candidate will work with newly developed toolbox technologies, advanced disease models including 3D cell cultures and in vivo systems, and integrated multi-omics and computational analyses. The project is well suited to a highly motivated student interested in virology, infectious diseases, imaging-based profiling, and data-driven biology. Applicants should hold an MSc in molecular biology, biomedical sciences, virology, bioengineering, or a related field. The position is intended for candidates eligible for an FWO PhD fellowship, meaning the MSc degree must have been obtained less than two years ago. Experience or strong interest in fluorescence microscopy, reporter assays, high-content imaging, image-based phenotypic profiling, computational biology, R/Python, image analysis pipelines, transcriptomics, multi-omics integration, cell culture, and molecular cloning will be advantageous. Strong independence, organization, scientific writing, and English communication skills are expected. The offer includes a full-time doctoral contract for four years, renewable annually upon positive evaluation, within a stimulating interuniversity environment with access to advanced virological technologies and collaboration with national and international partners. To apply, candidates should submit a motivation letter and the contact details of two referees via the KU Leuven application portal before 2026-08-06. For more information, contact Hendrik Jan Thibaut at [email protected].