Théophile Sanchez

I’m a postdoctoral researcher passionate about the intersection of computer science and biology. My work focuses on developing methods that combine deep learning and evolutionary models to analyze genomic data. I design and apply artificial neural networks to address complex questions in population genetics and ecology.

Over the years, collaborating with different research groups has also sparked my curiosity about many other topics from human population history and species conservation to marine biology and new sequencing technologies. I enjoy diving into new fields and connecting ideas across disciplines.

Background

I hold an MSc in Bioinformatics from the Institut National des Sciences Appliquées (INSA Lyon) and an MSc in Artificial Intelligence from the Université Claude Bernard Lyon 1. I completed my PhD in deep learning applied to population genetics within the Bioinfo and TAU teams at the Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), near Paris.

Alongside my doctoral research, I was also as a part-time lecturer at Université Paris-Saclay, where I taught courses in machine learning, computer science, and bioinformatics.

In 2022, I moved to Zurich for a two-year postdoctoral position at WSL and ETH Zürich, working in the Ecosystems and Landscape Evolution group on deep learning applications for environmental DNA (eDNA).

In 2025, I joined the Environmental Physics group at ETH Zürich, where I managed large-scale marine datasets for the AtlantECO project.

I am currently part of the Laboratory of Evolutionary Genetics at the University of Neuchâtel, where I leverage genomic language models to better understand evolutionary processes and identify unexpected or novel genomic variations.