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University of Vienna

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784 Projects, page 1 of 157
  • Funder: European Commission Project Code: 642294
    Overall Budget: 3,785,870 EURFunder Contribution: 3,785,870 EUR

    Theoretical Chemistry and Computational Modelling (TCCM) is emerging as a powerful tool to help in the rational design of new products and materials for pharmaceutical, chemical, energy, computer, and new-materials industries. To achieve this goal, it is necessary to go beyond the traditional electronic structure studies, and merge complementary techniques that are normally not available at a single research group. The research programme of the TCCM-EJD aims at applying computational modelling to problems demanded by the industry and with high societal relevance, namely Materials with special properties, Biomolecules for new therapies and Energy storage. The objective of the Joint Doctorate is to prepare future research leaders, able to develop and use multidisciplinary computational techniques (methods and software), with solid communication skills, with many contacts established through the intensive relationship with worldwide leading researchers of 12 European universities and 14 additional partners, including 7 industrial and spin-off companies. A Joint Doctorate in TCCM is already operative since 2011, based on a fully participative scientific discussion and assessment of all research projects with a clear interdisciplinary character and the direct participation of the non-academic sector. The training programme puts the emphasis in common training, including 3 annual International Workshops, 3 schools on High Performance Computing and 3 tutorials in new computer codes. Career development opportunities are enhanced with regular inter-sectoral activities, transferable skill education and career coaching.

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  • Funder: European Commission Project Code: 798332
    Overall Budget: 166,157 EURFunder Contribution: 166,157 EUR

    The aim of my research is to unravel one of the biggest unresolved problems in neuroscience: the function of sleep. Sleep is an essential aspect of our lives, the importance of which appears clear in pathological conditions where its normal patterns are disrupted. Moreover, it is an evolutionary conserved phenomenon. It has been described and characterized at levels, ranging from behavioural to neural and molecular, in different animal species. Despite its conservation, pointing to a fundamental function in animal survival, the reason for sleep is still debated. Different hypotheses have been raised, such as the energy hypothesis, the synaptic homeostasis hypothesis, and the clearance hypothesis; there is evidence to support each. However, no conclusive agreement on the main reason why sleep evolved has been reached. This is mainly due to the difficulty in integrating the above-mentioned levels of characterization in a single model organism. I will overcome this limitation by studying sleep homeostasis in the nematode Caenorhabditis elegans. Since sleep is a global process spanning the entire brain, full understanding of its regulations requires investigation at levels ranging from molecular mechanisms in single cells to brain-wide network activity. This is currently achievable only in C. elegans, providing a small anatomically mapped nervous system, advanced genetic tools, and a novel whole-brain imaging approach with single-cell resolution that was developed in my host lab. I will leverage on this approach, as well as a new quantitative behavioural paradigm for sleep homeostasis in adult worms, to study the brain-wide effects of sleep deprivation. To unravel the essential function of sleep, I aim to: I: Characterize adult C. elegans sleep by quantitative behavioural analysis and whole brain imaging. II: Identify the neural signature of sleep deprivation. III: Isolate the final signal communicating sleep propensity to sleep-promoting centres.

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  • Funder: European Commission Project Code: 101147618
    Overall Budget: 4,263,620 EURFunder Contribution: 4,263,620 EUR

    GO-Forward aims to develop a novel methodological approach to make more accurate pre-drilling predictions of geothermal reservoir properties and thus reduce the mining risk. Key to the GO-Forward approach is to simulate geological processes for pre-drill assessment of reservoir structure and properties, calibrated to geological or geophysical data, rather than extrapolating the properties from those data with geostatistical methods. To this end, GO-Forward focuses on extending and further developing, testing and demonstrating the added value of forward modelling methods originally developed for hydrocarbon exploration, including stratigraphic forward modelling (SFM), diagenesis forward modelling (DFM) and fracture network forward modelling (FFM), to be used for exploration in different geothermal settings of high relevance for Europe. First, the developed approaches will be tested and calibrated in areas with abundant subsurface information and production data, to prove conceptually the applicability of the methods and reproducibility of the results, to optimise and de-risk geothermal exploration. Calibrated model approaches are subsequently applied in areas with limited data availability to demonstrate their capability to increase pre-drill Probability of Success (POS). To support the workflow and further reduce exploration costs, GO-Forward advances ML-based and computational methods to enhance (existing) (sub)surface information for calibration, uncertainty quantification and data assimilation, and (upscaling) routines for flow simulation, DNSH, and techno-economic performance assessment for POS and Value of Information (VOI). In addition, GO-Forward addresses public awareness of geothermal developments already at the early stages of exploration. By including novel approaches to citizen engagement and stakeholder dialogue, we aim to increase the societal readiness level of geothermal exploration as the first step of geothermal developments.

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  • Funder: European Commission Project Code: 252881
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  • Funder: European Commission Project Code: 758015
    Overall Budget: 1,499,560 EURFunder Contribution: 1,499,560 EUR

    Over the past 150 years, non-territorial autonomy has been one of three models for dealing with linguistic or ethnic minorities within several European states. Compared with the other two, i.e. the recognition of minority rights as individual rights and territorial self-rule, non-territorial autonomy has received little attention. This project proposes to write the first history of non-territorial autonomy as an applied policy tool in minority protection and as an intellectual concept with a chequered history across Europe. Intellectuals, politicians, and legal scholars across the political spectrum from the far left to the far right supported this idea, although they were aware of the risks of strengthening national differences by promoting such a collective approach to minority protection. The project explores how this idea of granting cultural rights to a national group as a corporate body within a state, as a means of integrating diverse nationalities, travelled and transformed throughout the Habsburg Empire from 1850 to the present. We propose to 1) trace the development/circulation of theoretical conceptions and political applications of non-territorial autonomy within the Habsburg Empire, by mapping the networks of scholars as well as politicians who advocated for it; 2) explain the continuities in the development of the idea, and its manifestations in policies adopted by interwar Central and Eastern European nation states, where communists, socialists, liberals and fascists alike were able to translate elements of non-territorial autonomy into their ideologies and programs; 3) analyse the treatment of non-territorial autonomy, which was advocated by minority lobby groups, in international minority protection in the 20th century despite strong opposition to practices based on it by international organisations. We rely on a mixture of historiographical methods developed in nationalism studies to analyse the idea’s translation in entangled transnational spaces.

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