The general aim of this project is the development of advanced computational models that enable affordable yet accurate quantum mechanical calculations of the structure and thermophysical properties of atomic and molecular fluids adsorbed on nanostructured surfaces.The proposed method is based on the liquid density functional theory (to treat the nuclear quantum dynamics) with the first principle evaluation of the interaction forces employing state-of-the-art electronic structure methods. These models will be subsequently applied to the computational investigation of macroscopic quantum effects on the adsorption isotherms, the isotopic selectivity on adsorption, particle diffusion, etc, of helium and hydrogen fluids adsorbed in nanoporous materials. We will focus on the characterization (via computational screening) of the influence of the structural and electronic properties (e.g., the size and geometry of the pores, the specific surface area, the topology of the electronic states) on the capacities of nanom

The emergence of Life relied on the presence of key molecules like water and prebiotic molecules. The primitive objects of our Solar System (comets, asteroids), which formed in the disk of dust and gas surrounding the young Sun, are thought to have delivered them to Earth during heavy bombardments. Observations show that the deeply embedded Class 0 protostars also harbour a very rich chemistry in their inner regions. What occurs to the chemical composition between this early stage of the star formation process and the formation of planets, comets, and asteroids is unknown. Do the molecules detected in these young protostars survive or are they destroyed and reformed at a later stage before being incorporated into planets, comets, and asteroids? This ERC project aims to reconstruct the physico-chemical evolution from the deeply embedded protostellar stage to the planet forming disk stage, through multi-source analyses of high angular resolution observations combined with chemical modeling studies. I will investigate the evolution of complex organic chemistry and isotopic fractionation during the star formation process using interferometric observations (ALMA, NOEMA) of solar-type protostars. In addition, I will carry out numerical simulations with a state-of-the-art gas-grain chemistry code in order to interpret the observations as well as to characterize the impact of the physical conditions and their evolution (environment, grain growth and dust settling, episodic accretion) on the chemistry. This ERC project will lead to a new understanding of the evolution of the chemical composition from the earliest protostellar stage to the formation of the disk that will give birth to the planets, comets, and asteroids, while identifying the processes affecting the final composition of the disk. The observational work will require the development of innovative tools of interest for the astrochemical community that I will release publicly.

Pharmacogenomics is the study of genetic variability affecting an individual’s response to a drug. Its use allows personalized medicine and reduction in ‘trial and error’ prescribing leading to more efficacious, safer and cost-effective drug therapy. The U-PGx consortium will investigate a pre-emptive genotyping approach (that is: multiple pharmacogenomic variants are collected prospectively and embedded into the patients’ electronic record) of a panel of important pharmacogenomic variants as a new model of personalised medicine. To meet this goal we combine existing pharmacogenomics guidelines and novel health IT solutions. Implementation will be conducted at a large scale in seven existing European health care environments and accounts for the diversity in health system organisations and settings. Feasibility, health outcome and cost-effectiveness will be investigated. We will formulate European strategies for improving clinical implementation of pharmacogenomics based on the findings of this project.

This research project will develop novel tools to investigate the interactions between individuals and the behavioral and cognitive mechanisms that promote the emergence of collective intelligence in humans, by integrating methods from biology, physics, economics and social sciences. Economics and biology, two disciplines that study the behavior of living beings, have followed distinct routes to analyze the behavior of human groups. While macroeconomic models rely on complex individual behavior and study static equilibria and steady states, biologists tend to focus on simple individual behaviors to study population heterogeneities and complex group dynamics. Simultaneously, physicists have developed a powerful set of methods and mathematical models to study the dynamics of particle systems and are very recently being combined with behavioral heuristics borrowed from cognitive science. Merging experimental and theoretical work, we will investigate the mechanisms by which the processing of information between individuals lead to collective decisions, and the specific situations where individual behaviors and choices are affected by the group. We will design and execute specific experiments to study how human groups select alternative solutions to solve specific problems, where anticipation about future actions/events will be formulated under different conditions of information. The resulting mathematical models based on the experimental data, including behavioral and cognitive processes at the individual scale, will give access to the type of information needed by the group to become more efficient in solving a given problem. These models will be analytically and numerically studied by means of classical and novel tools of statistical physics, complex networks and game theory. The present project thus aims to combine insights and methods from diverse disciplines to deliver novel hybrid models to study the emergence of collective intelligence in social human systems.

The goal of the EARLYRIDERS project is to identify the geographic and temporal locus of modern horse domestication. It also focuses on the interplay between domestication and the increase of pathogen load in horses, and the role of epizootic transfer of human pathogens, especially plague. Horse domestication represents a turning point in human history, revolutionizing transport, trade, warfare, agriculture, and allowing humans to form larger, interconnected societies. Despite its importance for human history, this process remains poorly understood. Recent genome sequencing shows that the earliest archaeological remains of domestic horses are not the ancestors of modern domestic horses and that another, still unknown, wave of domestication forged the modern horse during the Early Bronze Age. Horse riding also allowed a rapid spread of diseases. For instance, the plague, that regularly haunted human populations in history, has been already commonly found in human remains dating to the Early Bronze Age. As the gene essential for the transmission through fleas was absent in these ancient strains, the plague might have been transmitted through other, still unknown vectors. This represents a serious gap in understanding of the early epidemiology of this important disease. As the spread of plague appears to be concurrent to horse domestication, the question remains whether the horse accounted for its spread, either as a vector or passively, by contagious riders. We aim at identifying the source of the second domestication wave and pathogen load in ancient horse populations by sequencing 300+ samples originating from all potential centers of domestication. Full genome sequencing is not possible due to low endogenous DNA content, therefore the samples will be subjected to sequence enrichment techniques, including the novel hyRAD method developed by the experienced researcher, scalable to thousands of loci in hundreds of samples at moderate cost.