Glass is one of the oldest materials of mankind with the oldest specimen dating back to 5000 BC. Interestingly, despite its age, the techniques for shaping glass have seen little progress within the last five centuries. Recent key achievements in three-dimensional printing has opened the door to the fabrication of complex glass based objects. Notably, high-resolution microstructures have been achieved by microstereolithography, but their resolution is not sufficient for many applications. This is mainly due to the inherent problems associated with one-photon absorption (1PP) based 3D Printing techniques such as the layer-to-layer structure. In this context, 3DGlass aims to explore the fabrication of glass based microstructures by 3D direct laser writing using two-photon polymerization (2PP). The latter offers unmatched degree of freedom coupled with resolutions no other manufacturing techniques can achieve. Being able to generate high-resolution 3D structures with a direct writing process would be a key enabling technology for several key technologies such as precision and microoptics. This project will explore nanocomposite glass precursors termed Glassomer which have been used for 1PP of glass and, very recently, have attracted interest for 2PP although neither resolution nor processing speeds expected from 2PP have been achieved. Furthermore, we will explore techniques which allow creating porous glass monoliths via 2PP, a technique which would open up the manufacturing of engineered-porous glass scaffolds for applications in separation science, catalysis and precision optics. The research hypothesis of this project is that, building on prior work of the two groups, it is possible to redesign Glassomer for high-resolution and high-speed structuring via 2PP. The objectives of the project are thus to create a nanocomposite formulation for 2PP structuring of porous or non porous glass at a resolution of 1 µm and processing speeds of 100 cm/s.

EUCOR – The European Campus of the upper Rhine area embracing French, German and Swiss regional universities has been created to form a cluster of excellence in higher education and research. The Upper Rhine Immunology (URI) group has been founded by teaching staff, clinicians and researchers of the EUCOR universities of Strasbourg, Freiburg and Basel to create such an excellence center in the discipline of immunology. The group organizes workshops and conferences and has made the first steps towards a joint Master. The MSCA-ITN-EJD EURIdoc will extend these operations of the URI-group towards a joint doctorate. EURIdoc will focus on (i) immune development and homeostasis, (ii) molecular basis of signaling, (iii) immunodeficiencies, (iv) auto-immune diseases and (v) innovations for therapy. Beyond academic research activity conjointly carried out in two universities, which is an integral part of the co-diploma MSCA-ITN-EJD program, EURIdoc will provide secondments in the private sector to reinforce inter-sectorial activity and to produce a favorable environment for industry. To make this initiative taken by the URI-group founders successful, further discussions are needed to (i) optimize the scientific and the educational strategies, (ii) finalize the consortium, (iii) obtain professional advice and (iv) prepare the institutional and administrative integration of the program. We therefore apply for financial aid of the MONTAGE DE RESEAUX SCIENTIFIQUES EUROPEENS OU INTERNATIONAUX (MRSEI). The expected outputs of EURIdoc are (i) high quality research with interdisciplinary aspects leading to high impact, open access publication and/or innovation (patent), (ii) excellent knowledge and know-how acquisition by doctoral candidates, (iii) better employability of the doctoral candidates in academia and in private sectors and (iv), all-in-all, increase the international visibility of the EUCOR – The European Campus as a major international European network of higher education and research sites for the benefit of France.

In this project, the consortium members will develop an automated system for cell culture optimization based on the combination of machine learning with Lab-on-a-Chip (LOC) technology. The benefits of microfluidics, coupled with the ability of machine learning to process the large amounts of data and variables of microfluidic systems, will lead to a unique, easy-to-use tool that will advance automation and precision levels for cell cultures. This new system will involve real-time monitoring of the state of a cell culture through the analysis of images by a machine learning algorithm. These parameters will then be provided to another agent, which will control the pumps that inject medium and reagents into the culture. Thereby, a closed-loop system completely controlled by machine learning is obtained, which will allow the automatic analysis of thousands of variables in a single test. To achieve this goal, the system will be based on the use of two main areas of machine learning. With supervised machine learning, annotated images of the cell cultures will be used to train an artificial neural network to automatically detect and distinguish individual cells from the image background. The individual detections allow to derive several accurate measurements such as cell count, cell area, morphology and other metrics, required for an accurate estimate of the cell culture state. ’Reinforcement learning’ is an area of machine learning which aims to learn optimal behavior in an environment with unknown dynamics. In the presented system, an algorithm will combine the state information extracted from the image analysis and the possibility to modulate the medium composition in order to optimize the state of the cell culture with respect to a user-defined metric (e.g., total cell area). The algorithm monitors the culture’s state while continuously re-adjusting the medium composition. Thereby, it learns about relations between cell culture state and media composition and will ultimately be able to derive a time and state-dependent behavior that optimizes the user-defined metric, resulting in an optimized cell culture growth as well as the corresponding protocol with which to achieve the former. Although this tool will be very valuable for all types of cultures, as particular applications and proof of concept for suspension as well as adherent cells, this system will be tested for the maintenance and growth of two central players of the immune response in the body and the central nervous system (CNS). Specifically, we plan to culture autologous T-cells (suspension cells) where the algorithm will optimize their production by defining the cytokine cocktail composition and schedule of administration; and culture microglial cells (adherent cells), the tissue-resident macrophages of the CNS, to assess neuro-inflammatory processes and therapies in neurodegenerative pathologies.

The Espace-Dev laboratory of the University of Guiana wishes to set up a Twinning project with three objectives: to increase skills in the intelligent management of the solar resource using artificial intelligence, to build a European scientific network and to improve support for the management of European projects. French Guiana, by its geographical location has a strong solar potential. Several aspects are essential for the proper management of this potential: estimation of sunshine, prediction of the availability of the resource, integration of the energy produced into the energy distribution system, etc. The research team has understood the interest of exploiting this resource, particularly in order to increase the energy transition and the energy independence of the territory. Thus, research is conducted in the laboratory not only on the estimation of irradiance from satellite images, which allow to obtain the irradiance at any location covered by the satellite, but also on the prediction of irradiance and energy production of photovoltaic power plants using methods of artificial intelligence. The setting up of a Twinning project will enable the university to network with leading European institutions. Three European institutions have been targeted for their concordance with the laboratory's project but also for their complementarity. The research center for energy, environment and technology, a research organization in Spain, will provide expertise in the estimation of irradiance from satellite images and the processing of time series. The University of Freiburg will be involved in the field of artificial intelligence. The institute of systems engineering and informatics: research and development in Lisbon with whom the collaboration will focus on the prediction of the production of photovoltaic plants. The networking with these institutions will allow the team to increase its skills in the above-mentioned fields. This network will help the research team to improve its skills in the selected themes and to increase its competitiveness on the European level. In addition, this project will allow the development of research management skills within the newly created European project support unit within the university. In addition, this project will enable the development of research management skills within the university's emerging European project support unit. The Twinning project will have scientific impacts at the local and regional level. The recognition of the laboratory by companies, whose field of action is solar energy, will allow the construction of CIFRE theses and expert missions. Moreover, the territory will radiate on the Guiana Shield and will become a reference in the themes addressed by the project.