Rare diseases (RD) are diseases that affect not more than 5 per 10 000 persons (according to the EU definition). 7000 distinct rare diseases exist, affecting between 6% and 8% of the population (about 30 million EU citizens). The lack of specific health policies for rare diseases and the scarcity of the expertise, translate into delayed diagnosis, few medicinal products and difficult access to care. That is why rare diseases are a prime example of a research area that strongly profits from coordination on a European scale. At present only few European countries fund research on rare diseases through specific dedicated programmes. Therefore, the funding of transnational collaborative research is the most effective joint activity to enhance the cooperation between scientists working on rare diseases in Europe and beyond. The E-Rare consortium was built to link responsible funding bodies that combine the scarce resources and fund rare disease research via Joint Transnational Calls (JTCs). The current E-Rare-3 project proposal will extend and strengthen the transnational cooperation by building on the experience and results of the previous E-Rare-1&2 programmes. The consortium comprises 26 institutions from 17 European, Associated and non-European countries. Its international dimension will be directly translated into close collaboration with IRDiRC and other relevant European and international initiatives. IRDiRC guidelines and policies will be implemented in the four JTCs and representatives of the IRDiRC Scientific Committees will be invited to join the Advisory Board of E-Rare-3. Members of the EUCERD group will be involved in identifying rare disease research needs. Patients’ organizations from Europe (represented by EURORDIS) and beyond will be invited as a key partner towards collaborative efforts for research promotion and funding. The collaboration with European Research Infrastructures will be consolidated to enhance efficient and participative research.

Climate change is one of the most urgent problems facing mankind. Implementation of the Paris climate agreement relies on robust scientific evidence. Yet, the uncertainty of non-greenhouse gas forcing associated with aerosol-cloud interactions limits our constraints on climate sensitivity. Radically new ideas are required. While the majority of forcing estimates are model based, model uncertainties remain too large to achieve the required uncertainty reductions. The quantification of aerosol cloud climate interactions in Earth Observations is thus one of the major challenges of climate science. Progress has been hampered by the difficulty to disentangle aerosol effects on clouds and climate from their covariability with confounding factors, limitations in remote sensing, very low signal-to-noise ratios as well as computationally, due to the scale of the big (>100Tb) datasets and their heterogeneity. Such big data challenges are not unique to climate science but occur across a wide range of data science applications. Innovative techniques developed by the AI and machine learning community show huge potential but have not yet found their way into climate sciences – and climate scientists are currently not trained to capitalise on these advances. The central hypothesis of IMIRACLI is that merging machine learning and climate science will provide a breakthrough in the exploration of existing datasets, and hence advance our understanding of aerosol-cloud forcing and climate sensitivity. Its innovative training plan will match each ESR with supervisors from climate and data sciences as well as a non-academic advisor and secondment and provide them with state-of-the-art data and climate science training. Partners from the non-academic sector will be closely involved in each of the projects and provide training in a commercial context. This ETN will produce a new generation of climate data scientists, ideally trained for employment in the academic and commercial sectors.

The overall aim of ATM4E is to explore the scope for the potential reduction of air traffic environmental impacts in European airspace on climate, air quality, and noise through optimization of air traffic operations The project will integrate existing methodologies for assessment of the environmental impact of aviation, in order to evaluate the feasibility of environmentally-optimized flight operations to the European ATM network, including climate, air quality, and noise impacts. A preliminary modelling concept for climate-optimization has previously been developed for an FP7 European Project, (REACT4C). The ‘case-study’ approach of REACT4C will be built upon and extended to a multi-dimensional environmental impact assessment, to cover climate, air quality and noise, to better understand impacts in the European airspace. Different traffic scenarios (present-day and future) will be analysed to understand the extent to which environmentally-optimized flights based on multi-dimensional environmental criteria (assessment) would lead to changes in air traffic flows and create challenges for ATM. The findings of the project will be used to prepare a roadmap that is consistent with SESAR2020 principles and objectives, which would consider the necessary steps and actions that would need to be taken to ultimately introduce environmentally-optimized flight operations in European airspace.