Professionnal experiences

Current

2026: Postdoc at Centre d’Enseignement et de Recherche en MathématIques et Calcul Scientifique. Subject: Computing transition rates: models and algorithms

December 2024 – December 2025: Postdoc at Institut des NanoSciences de Paris. Subject: Complex Phases in Ammonia-Water Mixtures Under Extreme Conditions: Disorder, Plasticity, and Super-Ionicity
December 2021 – November 2024: PhD at Institut des NanoSciences de Paris. Doctoral school: Physique en Île-de-France. Subject: Bayesian methods for studying Nuclear Quantum Effects in Material Science. Thesis available at https://theses.hal.science/tel-05389261v1

L. Maillard, F. Finocchi and M. Trassinelli. Assessing Search and Unsupervised Clustering Algorithms in Nested Sampling. Entropy, 25(2):347, Feb. 2023. https://doi.org/10.3390/e25020347
L. Maillard., P. Depondt, F. Finocchi, S. Huppert, T. Plé, J. Salomon and M. Trassinelli. Probing the Partition Function for Temperature-Dependent Potentials with Nested Sampling. The Journal of Chemical Physics, 163(18):184109, Nov. 2025. https://doi.org/10.1063/5.0293473

L. Maillard, F. Finocchi, C. Godinho, and M. Trassinelli. Nested Sampling for Exploring Lennard-Jones Clusters. In The 43rd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering; MDPI, p 8, Oct. 2025 https://doi.org/10.3390/psf2025012008

M. Trassinelli, L. Maillard. and C. Godinho (September 2025). nested_fit (Version 5.5). Github. https://github.com/martinit18/nested_fit