Jules Morand

Curriculum Vitae

Originated from the north-east of France, I did my two first years of studies in prep school of mathematics and physics in Nancy. I then joined the University of Orsay “Paris Sud XI”, where I studied fundamental physics. After one year of Erasmus studies at Imperial college London, I went back to Paris where I obtained in 2011, my Master in theoretical physics of complex systems. The same year, I started the Ph.D. program at <<Université Pierre et Marie Curie>> in Paris under the supervision of Michael Joyce and Pascal Viot. I worked notably on the theory and simulation of self-gravitating systems. In 2014, I defended my thesis entitled <<Dynamics of long rang system beyond the Vlasov limit>>.

In 2016, I was a post doc at the National Institute for Theoretical Physics in Stellenbosch University in South Africa in a group leaded by Hugo Touchette where I worked on large deviation theory applied to random walk on random graphs. We developed theory to compute the probability and generate rare events of random walk on networks.

Between 2017 and 2021, I was a post doc at the Biosystems and Integrative Science Institute at the University of Lisbon in group leaded by Patricia Faìsca working the physical basis of the dialysis related amyloidosis. I modified a molecular dynamic code of protein folding and managed several campaigns of long run simulations of the folding of beta2-microglobuline in order to have a better understanding on the generation of intermediate (partially unfolded) states crucial in the process of protein aggregation.

Since October 2021, I am part of the SBP group where I work on the development and applications of methods of statistical physics and information theory on complex networks to optimise the collection of data and the previsions in epidemiology, within the context of the project AIACE – Artificial Intelligence Tracking Algorithms of Covid-19 Epidemics, financed by the University of Trento.

Research interests

Theoretical Physics, Computational Physics, Statistical Mechanics, Complex Networks, Long range systems, Self-gravitating systems, Large deviation theory, Protein Folding, Machine learning.