Meet our team

Iris began her studies with a dual degree between Sciences Po Paris and Pierre and Marie Curie University, in political science and mathematics, a  choice driven by her taste for challenge and a desire to keep her horizons open. During this program, she studied in the United States as part of an exchange at Johns Hopkins University, where she discovered the application of mathematics to public health.

She then pursued a dual degree between Sciences Po and HEC, aiming to gain skills in management and strategy. 

After her studies, she joined the Boston Consulting Group, where she worked on various projects, including those in the healthcare sector. Invited to a seminar organized by Entrepreneur First, she met Chloé Geoffroy, marking the beginning of an adventure rooted in a shared vision: to be entrepreneurs, yes, but to transform reality. To make an impact.

Chloé Geoffroy is a pharmacist (Universite Paris Cite) and engineer in chemistry (Chimie ParisTech) with a deep passion for decoding the brain through an interdisciplinary lens that blends chemistry, mathematics and physics. During her PhD at the École Normale Supérieure she designed hybrid experimental-computational methods to control drug activity in time and space, by linking a molecule’s physicochemical traits to its biological micro-environment. The purpose: sharply reduce off-target actions and therefore side-effects -an early step toward safer brain therapeutics.

After her post-doctoral work, she wanted to put this expertise to work for a cause close to her heart: precision medicine, with the goal of reducing inequities in treatment response across patient populations. At just that moment, an invitation to an Entrepreneur First seminar introduced her to Iris Maréchal; recognizing their shared values and complementary skills, Chloé and Iris co-founded Theremia to turn their vision into reality.

Thaïs is Chief of staff at Theremia. After completing a preparatory program in economics, she joined ESCP Business School, where she specialized in deeptech entrepreneurship. Before joining Theremia, she held several Product Manager positions in diverse tech environments, allowing her to build solid expertise in product development and team management.

Senior Machine Learning Engineer with a robust foundation in both microelectronics and biomedical engineering, holding degrees from Telecom Paris and Imperial College London. He developed deep expertise in data science and data engineering through strategic projects in Machine Learning. At Theremia, Jean leads the development of the pharmacological algorithm, leveraging his skills in modeling, machine learning, and data processing.

Federico joined Theremia as a Research Scientist, where he works on PK/PD modelling and develops algorithms for personalized drug administration. He holds a background in Mathematical Engineering, and earned  a PhD in Statistics from Bocconi University, where he focused on Bayesian modelling for complex data structures.  He then pursued a postdoctoral fellowship at the Ceremade laboratory at Université Paris-Dauphine. His academic path, at the intersection of applied mathematics and data science, has provided him with deep expertise in probabilistic modeling, which he now applies to challenges in precision medicine.

Margaux graduated from an engineer school, Mines  Nancy, and then joined the MVA (Mathematics, Vision, Learning) master’s programme at ENS Paris-Saclay where she studied machine learning, computer vision and neuroscience. After several years of experience as a Data Scientist Consultant she joined Theremia. Her strong academic background and expertise in data science applied to real world data (RWD), now allow her to contribute to the field of precision medicine.

After completing a preparatory program in mathematics and physics, Lola was admitted to École des Ponts ParisTech. She then joined the prestigious Master’s program in Mathematics, Vision and Learning (MVA) at ENS Paris-Saclay, a leading course in applied mathematics, artificial intelligence, and data science. She also completed a software development internship at Amazon, a technically demanding environment focused on infrastructure, code quality, and optimization. At Theremia, she works on the patient algorithm for Parkinson’s disease. By combining medical data with predictive models, she explores how to fine-tune treatment parameters,  such as dosage, frequency, and formulation,  to match each patient’s individual profile. Her work draws on AI techniques and biomedical modeling approaches to support more personalized and adaptive care strategies.

Pau joined Theremia as part of his final-year internship for the prestigious MVA Master’s program (Mathematics, Vision, Learning) at ENS Paris-Saclay, a leading program in applied mathematics, artificial intelligence, and data science. Prior to that, he completed a dual Bachelor’s degree in Data Science and Mathematics in Barcelona. Throughout his academic journey, Pau completed internships in numerous research institutions, such as a 9-month internship at the Massachusetts Institute of Technology (MIT) , during which he successfully carried out complex, real-world projects. These experiences strengthened both his technical expertise and his problem-solving abilities. This outstanding academic and professional background now enables him to make a strong contribution to Theremia’s research and development projects, bringing real added value.

Mathieu Even is a postdoctoral researcher at INRIA Montpellier since October 2024, working in the premedical project on causal inference and policy learning from medical data. He completed his PhD in 2024 at INRIA Paris and ENS Paris, with a thesis focused on decentralized, asynchronous, privacy-preserving, and personalized federated learning. He also holds a Master’s degree in Probability and Statistics from Université Paris-Sud and conducted research at Microsoft Research during an internship.

Titouan joined Theremia as a Data Scientist after graduating from CentraleSupélec, where he built a strong foundation in engineering, applied mathematics, and data science. He pursued his final year at Imperial College London in the MSc Health Data Analytics and Machine Learning program, a course at the crossroads of AI, biostatistics, and medical research. During his master’s thesis, he focused on the clustering of metabolites, exploring how unsupervised learning can reduce the dimensionality of metabolomics data while uncovering biological patterns to support biomarker discovery. With these experiences at the interface of machine learning and biomedical data, he now works at Theremia on developing algorithms based on PK/PD modeling to improve personalised drug administration.

Clément graduated as a digital engineering student from Télécom SudParis and completed the Master’s program in Data Science at École Polytechnique, where he studied machine learning, deep learning, and natural language processing. He then worked as a Data Scientist Intern at WhiteLab Genomics, where he designed LLM and RAG-based solutions for genomic data enrichment and contributed to R&D projects in bioinformatics. Building on this experience at the intersection of AI and biomedical research, he now applies his expertise in machine learning and data modeling to the development of Theremia’s pharmacological algorithm, aiming to better characterize treatment response

Gaëtan graduated from École des Ponts ParisTech where he built a solid foundation in applied mathematics, probabilities and statistics, after which he joined the MVA (Mathematic Vision Learning) Master's program at ENS Paris-Saclay where he studied machine learning, data science and computer vision. Prior to joining Theremia, he completed multiple internships both in startups as a data analyst and in research institutions. At Theremia, he works on the patient algorithm, using his skills in machine learning to help gather insights from real world data in order to match patients to the treatment that's best for them.