Your aim will be to develop novel AI-driven algorithms that can extract two key spatial features from tissue sections: (i) the fundamental morphological and pathological features of the tissue (tissue architecture) and (ii) the spatial organization of the cells representing the building blocks of the tissue of interest, including their precise identities and activation states (cellular organization). To achieve this goal the host labs are developing spatial multi-omics technologies
PhD in Bioinformatics, Computational Biology, Statistics, Computer Science, Artificial Intelligence, Physics, Engineering, Bio-engineering, or equivalent.
Proven track record of successful research and high ranked publications in bioinformatics
Experience with applying AI (deep learning, probabilistic modelling, generative AI) or machine learning in the field of systems biology
Proficient in Python or R programming
Preference will be given to candidates with experience with
processing spatial omics data
high-performance computing and software containers
Strong communication skills in English
Strong interpersonal skills
Ready to be the key link between multiple researchers
Online application through saeyslab.sites.vib.be/en/jobs