Ferruz Lab

Ferruz LabFerruz Lab

Systems and Synthetic Biology

Ferruz Lab
AI for Protein Design
Group leader

Ferruz Lab

AI for Protein Design
Group leader
We are offering a fully-funded PhD position in our lab

 

2024 - Group Leader at the Centre for Genomic Regulation (CRG), Barcelona (Spain)
2023 - Group Leader at the Institute of Molecular Biology of Barcelona (IBMB), Barcelona (Spain)
2022 - Beatriu de Pinós Fellow, University of Girona, Girona (Spain)
2017 - Postdoc at University of Bayreuth, Bayreuth (Germany)
2016 - Researcher at Acellera Labs, Barcelona, (Spain) and Postdoc at Pfizer, Cambridge (USA)
2016 - PhD in Biomedicine, University Pompeu Fabra (Spain)
2013 - MSc in Bioinformatics for Health Sciences, University Pompeu Fabra, Barcelona (Spain)
2011 - MSc in Chemistry, Erasmus program, University of Cambridge (UK)
2010 - BSc in Chemistry, University of Zaragoza (Spain)

News

CRG researchers to build generative AI model for synthetic proteins (06/09/2024)
Researchers at the Centre for Genomic Regulation (CRG) have begun efforts to build ATHENA, a generative artificial intelligence which can design proteins with custom properties.

Q&A with Noelia Ferruz, Group Leader of Artificial Intelligence for Protein Design (23/07/2024)
She has recently joined the Centre for Genomic Regulation (CRG) and opened a new group dedicated to the development of protein language models that can create custom-designed proteins. The proteins can help us tackle a variety of complex problems in healthcare, agriculture, climate change and industrial applications.

Summary

Our research group is focused on using computational and experimental approaches to understand and design protein functions. We have extensive experience in deep unsupervised learning and protein design, which we have applied to various projects (see https://www.aiproteindesign.com).
Over the next few years, we will expand our focus to include the design of custom-tailored and new-to-nature protein functions. We will implement models, understand their decision making process using XAI and improve their performance through reinforcement learning. We will also include experimental characterization efforts, allowing continual improvement of our models.
We are particularly interested in using our expertise to address significant challenges in the fields of healthcare and sustainability. This includes developing new proteins to treat diseases, designing enzymes for biotechnological applications, and creating proteins with novel functions that can help address environmental challenges.
We believe that protein design has the potential to change the world we live in, and Artificial Intelligence is at the core of this revolution.