Numerous advances impacting society, from basic science to consumer technology, are built on fundamental research in mathematics. Examples include non-Euclidean geometry (leading to general relativity, and then GPS navigation); number theory (leading to public-key cryptography, and then to secure online commerce); and topology (with applications in image recognition and medical diagnostics). This doctoral network, ReMoLD: Representations, Motives and Langlands Duality, will advance fundamental research in three highly active fields of mathematics: representation theory, algebraic geometry and number theory. Specifically, ReMoLD is at the forefront of research in geometric representation theory and the Langlands program using recent mathematical innovations from the field of motives. ReMoLD will build a European network of doctoral candidates that excels in fundamental research in mathematics, implements innovative training formats and partners with a leading European quantum computing company, in order to form a group of scientists ready to apply to highly competitive positions in academia and industry.

The adoption of green energy technologies worldwide is going to have significant consequences for mineral demand in a near future. The booming sector of artisanal and small-scale mines (ASM) that employs around 40 million people, represents about 20% of the global gold and diamond supply, 25% of tantalum and tin, and up to 80% of sapphire. Those numbers make the ASM sector a pivotal actor in the energy transition. The aim of ArtiMinDev project is to analyze the economic and social impacts of ASM in sub-Saharan African countries. Up until now, the absence of exhaustive time-varying information on the location of ASM has prevented researchers in social sciences from precisely quantifying the contribution of this activity to economic development. The ambition of this project is twofold. First, I intend to map the opening/closing of ASM in sub-Saharan African countries over the period 2000-2020 with exact information on location (GPS coordinates). Two other crucial information are also collected: the size and the mineral extracted from each ASM. I will use machine learning techniques and satellite image time series to identify sediment and open pit-mining activities. Second, equipped with this ground-breaking dataset, I aim to provide systematic and large-scale evidence of the impact of ASM on violence and conflict; environmental degradation and health; and internal migration. The proposal’s objectives, grounded in quantitative economics, are spanning several literatures from a wide variety of disciplines, by combining state-of-the-art machine learning techniques and remote sensing data. I expect the methodologies and the results to push the research frontier in several dimensions. Moreover, the conclusions drawn from the project would be highly relevant for policy-makers and NGOs aiming to improve the monitoring of those mining activities and their impacts on conflict, health and environmental degradation.

As the society’s need for energy is increasing, climate change points towards the need of finding sustainable renewable energy sources. Biogas holds the potential to replace natural gas as energy carrier, thus reducing the reliance on fossil fuels while introducing renewables as drop-in solution to existing infrastructure. However, existing technologies for the removal of carbon dioxide from biogas are energy intensive and considerably decrease the overall efficiency of biomethane as energy carrier. The aim of the project Porous Ionic Liquids for Sustainable Energy (PILSEN) is to improve the energy efficiency of biomethane production from biogas while lowering the carbon footprint. We will achieve this by capturing carbon dioxide during the purification of biogas and using it as a source of carbon. We propose to develop a versatile chemical platform for carbon dioxide removal from biogas, together with the subsequent conversion to value-added chemicals. This chemical platform will be based on porous ionic liquids, which are a new and promising class of materials for processes involving gases. Preliminary results confirm that porous ionic liquids show carbon capture performances similar to benchmark technologies allowing for simultaneous capture and utilization with minimum energy cost. The design flexibility and low environmental impact of ionic liquids bears great potential for the tuneability of our chemical platform. Hence, we will combine theoretical and experimental approaches to identify porous ionic liquids suitable for carbon capture and conversion including the energy-efficient isolation of products.

Rare earth elements (REE) and transition and post-transition metals (TM) are essential to modern life, yet we know little about how they concentrate at Earth’s surface, especially on the seafloor, which holds vast reserves. The DEEP-SEE project will shift paradigms on marine metal deposits from chemical composition and resource inventories to a holistic view based on atomic-scale observations and modeling. This research will determine geochemical processes that give rise to some of the highest metal partitionings in supergene ores. First, crystal chemistry of 3+ REE in biogenic vs. authigenic sedimentary apatite is proposed as a new proxy for the paleoceanographic enrichment setting with the potential to become an indicator for future exploration sites. Second, crystal chemistry of 3+ REE will elucidate the scavenging history of Fe-Mn crusts and corresponding evolution of seawater REE as recorded in growth layers over millions of years. Third, investigation of the redox chemistry and mineralogy of Fe-Mn crusts and nodules will explain how the redox-sensitive metals Co, Ce, Tl, and Pt are enriched from 109 to 106 times relative to seawater. To date, these processes have been impossible to interrogate because of analytical challenges posed by the multi-elemental composition and mineralogical heterogeneity of seafloor deposits. A promising approach for tackling these challenges is new micro-X-ray emission spectroscopy using a unique high-luminosity compact XES spectrometer at the European Synchrotron Radiation Facility. Installation of the spectrometer on a microfocus beamline under construction on the new 4th generation ESRF X-ray source will provide a momentous gain of at least 100 in detection limit and unprecedented sensitivity and precision in the analysis of REE and TM. More broadly, the research will show how new knowledge about Earth processes can be obtained with a fresh look at individual trace elements previously inaccessible by crystal chemical study.

Understanding the fundamental basis of brain disorders is a one of the greatest challenges of the 21st century. Large-scale genetic studies have identified numerous genes with associated roles in both neurodevelopmental and neurodegenerative disorders, suggesting that common mechanisms are involved in the different phases of the same disease. Autophagy is such mechanism, which dysfunction during development or in adult can lead to neurodegenerative diseases, including beta-propeller protein-associated neurodegeneration (BPAN). BPAN is a disease caused by loss-of-function mutations of the autophagy-related gene Wdr45 resulting in neurodevelopmental defects and neurodegenerative phenotypes. Although BPAN is a rare disease, it represents a genetically simple model to understand the contribution of developmental defects during neurodegenerative disease. To answer these questions, we will use Drosophila that provides unequaled experimental power for generating models of human neurological diseases and establishing their molecular genetic basis. Here, using CRISPR/cas9-made Wdr45 null mutant flies generated by Mollereau and col., I examined human Wdr45-linked phenotypes in Drosophila. I found adult-onset neurodegenerative phenotypes including age-related locomotion decline as well as an abnormal hyperkinetic movements in the embryos of Wdr45 mutants. Therefore, targeting Wdr45 in Drosophila, we aim not only to allow identifying the developmental and neural basis of autophagy-associated neurodegeneration, but also to uncovering the disease molecular responses that are prior to the appearance of neurodegenerative syndromes. Ultimately, findings of our proposal can help find early disease biomarkers and design therapies for broad range of neurological disorders.