Anne-Florence Bitbol

Biography Awards Teaching & PhD

I was trained in physics, and always had a strong interest in biology. I am broadly interested in understanding biological phenomena in a quantitative way, through physical concepts and mathematical and computational tools. I investigate the relative impacts of optimization and historical contingency in biological evolution, both at the scale of protein sequences and at the scale of microbial populations.

Here is my research group website.

Curriculum vitae

Here is my complete CV.

Professional experience:

Since 2020: Tenure-Track Assistant Professor, Institute of Bioengineering, School of Life Sciences, EPFL, Switzerland
2016-2020: CNRS Researcher (tenured), Laboratoire Jean Perrin, Sorbonne Université, France
2012-2016: Postdoctoral Research Fellow, Biophysics Theory Group (PIs: Ned Wingreen, William Bialek, Curtis Callan), Princeton University, USA

Education:

2009-2012: PhD in Physics, summa cum laude, Université Paris-Cité (Paris-Diderot), France, "Statistics and dynamics of complex biological membranes", advised by Jean-Baptiste Fournier
2007-2009: MSc in Physics, summa cum laude, ENS, Paris, France
2006-2007: BSc in Physics, summa cum laude, ENS Lyon, France

Awards

Reviewer Excellence award

American Physical Society

2025

Early Career Scientist Prize in Biological Physics

International Union of Pure and Applied Physics (IUPAP)

2023

Best teacher award

Life Sciences Engineering teaching section, EPFL

2023

Best teacher award

Life Sciences Engineering teaching section, EPFL

2023

Michelin Young Researcher (PhD) Prize

French Physical Society

2014

Louis Forest PhD Prize in the Life Sciences

Chancellery of the Universities of Paris

2013

Young Scientist Prize in Biological Physics

International Union of Pure and Applied Physics (IUPAP)

2023

Teaching & PhD

Current Phd

Alexandre Didier Nicolas Littiere, Agathe Bredel, Anamay Ashwin Samant, Cecilia Fruet

Past Phd As Director

Nicola Dietler, Richard Marie Servajean, Damiano Sgarbossa

Courses

EDCB seminar series

BIOENG-606

The EDCB seminar series provides EDCB students the opportunity to share their research and learn from their peers. Students can freely exchange, present data, ideas and get useful feedback on ongoing research and improve communication skills.

Genomics and bioinformatics

BIO-463

This course covers various data analysis approaches associated with applications of DNA sequencing technologies, from genome sequencing to quantifying gene evolution, gene expression, transcription factor binding and chromosome conformation.

Lecture series on scientific machine learning

PHYS-754

This lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting knowledge from data computationally and in an automatized way. We will learn on examples how this is influencing the very scientific method.

Randomness and information in biological data

BIO-369

Biology is becoming more and more a data science, as illustrated by the explosion of available genome sequences. This course aims to show how we can make sense of such data and harness it in order to understand biological processes in a quantitative way.