VIB.AI | AI in Biology

AI IN BIOLOGY

VIB.AI studies fundamental problems in biology by combining machine learning with in-depth knowledge of biological processes. We work towards foundation models and integrative theories of biological systems, and towards innovative AI-driven biotech applications in synthetic biology, agro-tech, and personalized medicine. 

Open group leader positions

We are recruiting multiple faculty members, junior to senior levels, who use and develop artificial intelligence methods and mechanistic mathematical models to address fundamental questions in biology.

We are currently reviewing applications and will open a second call in the fall of 2024. 

AI in biology

We welcome applications across all domains of machine learning, artificial intelligence, and associated fields. Examples include:

  • new AI architectures for biology and hybrid models that combine deep learning with mechanistic models;
  • foundation models of genome regulation using single-cell and spatial multi-omics data;
  • AI-based modeling of protein structure and protein interaction networks;
  • AI-based modeling of cell morphology and tissue function using imaging and computer vision;
  • AI models of disease and digital twin applications. 

 

Broad application space

Biological applications of your research can be broad: from microorganisms to plant biology, biodiversity and ecology, neuroscience, cancer, and immunology. We also welcome applicants with applied projects, including synthetic biology, AI-driven experiments (experiment-in-the-loop), or bio-engineering.

Our offer

The positions come with full salary and core funding (internationally competitive package) that is renewable for multiple additional 5-year periods, and access to state-of-the-art research and top-notch support core facilities, as well as support to attract talented PhD students and postdocs from across the world.

Connecting expertise

VIB.AI connects expertise in quantitative biology within VIB and beyond. 

One of the aims of VIB.AI is to connect existing expertise in quantitative biology already present within VIB, and to facilitate interactions across the institute.
christine durinx
Christine Durinx
Managing director VIB
AI models trained on large biological datasets can greatly accelerate discovery in life sciences. Today, high-throughput technologies and data science are steering biomedical research, and by launching VIB.AI we want to be at the forefront of this revolution.
Stein Aerts
Stein Aerts
Director VIB.AI