Resume

PhD candidate specialized in machine learning for drug discovery, with an emphasis on improving exploration and exploitation during lead optimization. Conducting my research within the Theoretical Chemistry Group at ENS-PSL and the Integrated Drug Discovery team at Sanofi. I am also pursuing an MBA at the Collège des Ingénieurs and teaching at ENS-PSL and Le Wagon bootcamp.


Education

Doctor of Philosophy - PhD 10/2022 – Present

École Normale Supérieure (ENS Ulm) Paris, France
Conducted research on machine learning applications in drug discovery and theoretical chemistry, in collaboration with Sanofi. Under the supervision of Pr. Rodolphe Vuilleumier (ENS) and Dr. Marc Bianciotto (Sanofi).

Master of Business Administration - MBA 01/2023 – Present

Collège des Ingénieurs (CDI Paris) Paris, France
Selective MBA program designed for top graduates from leading French Engineering Schools.

Master of Science - MSc 09/2021 – 09/2022

BME Paris - PSL University Paris, France
Relevant courses: Deep learning and neurosciences - Deep learning and neurocomputational projects - Quantification for Neuroimaging - Machine Learning for Bioimaging

Master of Science (“Diplôme d’ingénieur”) - MSc 09/2018 – 09/2021

ESPCI Paris Paris, France
Biotechnology specialization (3rd year): Systems biology and neurobiology - Biochemistry and molecular biotechnology - Deep learning - Statistical learning - Advanced analytical chemistry

Bachelor of Science - BSc 09/2016 – 09/2018

Sorbonne University Paris, France
Dual bachelor’s degree with majors in physics and chemistry.

Experience

Research scientist (CIFRE PhD) 10/2022 – Present

Sanofi Paris, France
  • Developed rational exploration and exploitation strategies for molecule prioritization during the lead optimization phase, supported by a comprehensive toolkit for medicinal chemists.
  • Simulated active-learning based selection scenarios on legacy drug discovery projects.
  • Developed QSAR/QSPR models in low and high data regimes.

Research intern 02/2022 – 09/2022

Aramis LAB (INRIA & Paris Brain Institute) Paris, France
  • Developed deep learning algorithms using graph neural networks for automated segmentation of peptide accumulation in whole-slide images, enabling improved stratification of Alzheimer’s disease patients.

Research intern 04/2021 – 08/2021

LSABM (ESPCI Paris - PSL) Paris, France
  • Developed a LC-MS method to detect mustard gas-modified DNA traces in biological samples, in collaboration with the French Defence Procurement Agency.

Analytical scientist intern 07/2020 – 12/2020

Adocia Lyon, France
  • Developed and characterized (via HPLC and NMR) a protective hydrogel for islets of Langerhans (beta cells) as part of a cell therapy project aimed at creating an artificial pancreas.

Research intern 06/2018 – 08/2018

Phenix Lab (CNRS) Paris, France
  • Investigated water dynamics in 15th-century paintings through NMR relaxometry, X-ray, and IR spectroscopy.

Data analyst intern 05/2017 – 08/2017

Development Alternatives Incorporated Washington DC, USA
  • Developed data visualization dashboards and contributed to a report for the Aspen Institute : “A Global Opportunity: Get Youth Working”.

Skills

Tools Python (scikit-learn, PyTorch, Tensorflow, RDKit, deepchem…), Git, AWS, Matlab, SQL

Communication French (native), English (fluent - C1 level), Spanish (intermediate - B1 level)

Extracurricular activities

  • Treasurer of the ESPCI Paris – PSL student’s office, in charge of a 150 000€ budget.
  • External Relations Officer of the ESPCI Paris – PSL sports union.
  • Sports: Handball (15 years, two-time high-school champion of Morocco), Diving (PADI 2), Skiing, Squash.