About Me
Background summary
Born and raised in Bilbao, Spain, I moved to the UK to study a BSc in Biochemistry at UCL, where I specialised in computational biology. During my degree, I also gained experience in protein science through a year-long Industrial Placement in Biophysics at Nxera Pharma (formerly Sosei Heptares).
My passion for mathematical modelling led me to specialise further through an MRes in Bioinformatics and Theoretical Systems Biology at Imperial College London, funded by a Basque Excellence Scholarship. There, I joined the Theoretical Systems Biology research group, where I worked on information-theoretical tools for RNA-seq data analysis and benchmarked simulation-based inference techniques. I was also part of the top-scoring team in the European Space Agency (ESA) Space Omics Hackathon, which granted us funding for a publication, and led to an ongoing collaboration.
I then joined the University of Cambridge and the Wellcome Sanger Institute after receiving a fully-funded PhD Studentship from Wellcome. I carried out rotations on fine-tuning DNA language models and interpretability of DNA foundation models. I then started my main project as part of the Marks Lab on AI-driven functional protein design, also collaborating with the Lehner Lab, Sander Lab, and other groups internationally.
In my free time I like to play tennis (for Jesus College Cambridge), lift weights, try new food and listen to all kinds of music genres.
Research Experience
PhD Student
Wellcome Sanger Institute & University of Cambridge
10/2024 - Present
My project consists of using and developing AI methods to design better proteins with de novo and natural functions. For this I am leveraging sequence-level information learned from evolution as well as structural information, drawing on methods and expertise from the Marks, Lehner and Sander groups. I am also part of the EVEdesign team, an initiative to democratise AI-driven protein design that enables building complex design pipelines and their integration with experimental data.
I co-founded and currently lead the Sanger Machine Learning Boocklub, a community of nearly 100 people where we run workshops, study sessions, Journal Club-style sessions and talks on the theory behind AI tools in biological research.
I previously carried out rotations on fine-tuning DNA language models (supervised by Leo Parts) and using Gaussian Processes for interpretability of DNA foundation models (AI for Cell Engineering Lab, supervised by Mo Lotfollahi). The poster from the former rotation won the Best Poster Award across the PhD cohort.
Graduate Researcher (MRes)
Imperial College London & The Francis Crick Institute
01/2024 - 09/2024
As part of the Theoretical Systems Biology group at Imperial College London, and in collaboration with the Briscoe Lab at the Crick, I improved existing and developed novel information-theoretical tools for single-cell RNAseq data analysis. Part of this work is being prepared for publication. Prior to that, I worked on a project aiming to benchmark deep learning methods for Bayesian Inference to parametrise models of gene regulatory networks. Both projects achieved a Distinction within the MRes in Bioinformatics and Theoretical Systems Biology at Imperial College.
Undergraduate Researcher (BSc)
UCL
01/2023 - 05/2023
During my final undergraduate year I carried out a Metagenomics Research Project investigating the effect of the microbiome composition on neurodegenerative disease incidence and progression, and trained diagnostic Machine Learning models for disease prediction. I also completed a Literature Project on network biology for Alzheimer’s Disease biomarker discovery, supervised by Prof Christine Orengo. Both projects achieved a High First within the BSc in Biochemistry.
Industrial Placement Student in Biophysics
UCL and Nxera Pharma
09/2021 - 08/2022
I gained significant wet and dry lab experience specialised on Cryo-EM whilst working within the Biophysics department in the Biomolecular Structure Team. In collaboration with the rest of the team, we solved the first-ever structures of a challenging drug target. I improved my teamwork and presentation skills, and my project was awarded an Exceptionally High First.
Professional Development
Certifications
All courses were completed in Coursera, and vary in duration from 8 to 120 hours. Course content and details can be found by clicking on each credential link.
Mathematics for Machine Learning: Multivariate Calculus (Credential)
Imperial College London 2023
Mathematics for Machine Learning: Linear Algebra (Credential)
Imperial College London 2023
Data Science Specialization: Statistics and Machine Learning (Credential)
The Johns Hopkins University 2022
Machine Learning with Python (Credential)
IBM 2023
Deep Neural Networks with PyTorch (Credential)
IBM 2023
Data Analysis with Python (Credential)
IBM 2023
Python for Data Science and AI (Credential)
IBM 2023
Workshops, Training and Hackathons
Gaussian Process and Uncertainty Quantification Summer School
University of Manchester, University of Cambridge 2025
ESA Space Omics Hackathon (Top Score)
European Space Agency 2024
Interpretable AI Hackathon
Society for Technological Advancement 2025
Skills
Technical strengths
Non-technical strengths
Programming Languages
Python
R
C++
JavaScript
Computational and Data Science Tools
PyTorch
GPyTorch
Git
Snakemake
Spoken Languages
English
Spanish
Basque
French
Awards & Recognition
For award details, please visit Awards on LinkedIn.
Best PhD Poster Award
Wellcome Sanger Institute 2025
Wellcome PhD Scholarship
Wellcome Sanger Institute
2024
Scholarship of Excellence
Diputación Foral de Vizcaya
2023
Ranked 1st of UG cohort
UCL Department of Biochemistry 2023
Dean’s List
UCL Department of Biochemistry 2021, 2023
UG Microbiology Prize
Microbiology Society
2021
Sir Jack Drummond Prize
UCL Department of Biochemistry 2021
Margaret Kerly Award
UCL Department of Biochemistry 2021
Faculty Education Award
UCL Faculty of Mathematical and Physical Sciences 2020