Zagreb, Croatia

Ruder Boskovic Institute

www.irb.hr
Zagreb, Croatia

The Ruđer Bošković Institute is a research institute located in the Šalata neighborhood of Zagreb, Croatia, founded in 1950, which studies the science.It is the largest Croatian research institute in the fields of the natural science and technology. The name of the institute, which honours the scientist Ruđer Bošković, was put forth by one of its founders, physicist Ivan Supek.The institute has a multidisciplinary character: it employs 550 academics and students from the fields of experimental and theoretical physics, chemistry and materials physics, organic and physical chemistry, biochemistry, molecular biology and medicine, environmental and marine research and computer science and electronics.Within Croatia, RBI is a national institution dedicated to research, higher education and provision of support to the academic community, to state and local governments and to technology-based industry. Within the European Union, RBI forms a part of the European Research Area. Worldwide, RBI collaborates with many research institutions and universities upholding the same values and vision.Approximately 90% of the institute's funding is provided by the Government of Croatia, through the Ministry of Science, Education and Sports. Wikipedia.


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Grant
Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2013.9.5 | Award Amount: 2.29M | Year: 2014

The need for machine learning (ML) and data mining (DM) is ever growing due to the increased pervasiveness of data analysis tasks in almost every area of life, including business, science and technology. Not only is the pervasiveness of data analysis tasks increasing, but so is their complexity. We are increasingly often facing predictive modelling tasks involving one or several of the following complexity aspects: (a)structured data as input or output of the prediction process, (b)very large/massive datasets, with many examples and/or many input/output dimensions, where data may be streaming at high rates, (c)incompletely/partially labelled data, and (d)data placed in a spatio-temporal or network context. Each of these is a major challenge to current ML/DM approaches and is the central topic of active research in areas such as structured-output prediction, mining data streams, semi-supervised learning, and mining network data. The simultaneous presence of several of them is a much harder, currently insurmountable, challenge and severely limits the applicability of ML/DM approaches.The proposed project will develop predictive modelling methods capable of simultaneously addressing several (ultimately all) of the above complexity aspects. In the most complex case, the methods would be able to address massive sets of network data incompletely labelled with structured outputs. We will develop the foundations (basic concepts and notions) for and the methodology (design and implementation of algorithms) of such approaches. We will demonstrate the potential and utility of the methods on showcase problems from a diverse set of application areas (molecular biology, sensor networks, mutimedia, and social networks). Some of these applications, such as relating the composition of microbiota to human health and the design of social media aggregators, have the potential of transformational impact on important aspects of society, such as personalized medicine and social media.


Grant
Agency: European Commission | Branch: H2020 | Program: COFUND-EJP | Phase: EURATOM | Award Amount: 856.96M | Year: 2014

A Roadmap to the realization of fusion energy was adopted by the EFDA system at the end of 2012. The roadmap aims at achieving all the necessary know-how to start the construction of a demonstration power plant (DEMO) by 2030, in order to reach the goal of fusion electricity in the grid by 2050. The roadmap has been articulated in eight different Missions. The present proposal has the goal of implementing the activities described in the Roadmap during Horizon 2020 through a joint programme of the members of the EUROfusion Consortium. ITER is the key facility in the roadmap. Thus, ITER success remains the most important overarching objective of the programme and, in the present proposal the vast majority of resources in Horizon 2020 are devoted to ensure that ITER is built within scope, time and budget; its operation is properly prepared; and a new generation of scientists and engineers is properly educated (at undergraduate and PhD level) and trained (at postdoctoral level) for its exploitation. DEMO is the only step between ITER and a commercial fusion power plant. To achieve the goal of fusion electricity demonstration by 2050, DEMO construction has to begin in the early 2030s at the latest, to allow the start of operation in the early 2040s. DEMO cannot be defined and designed by research laboratories alone, but requires the full involvement of industry in all technological and systems aspects of the design. Specific provisions for the involvement of industry in the Consortium activities are envisaged.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: EINFRA-2-2014 | Award Amount: 13.13M | Year: 2015

OpenAIRE2020 represents a pivotal phase in the long-term effort to implement and strengthen the impact of the Open Access (OA) policies of the European Commission (EC), building on the achievements of the OpenAIRE projects. OpenAIRE2020 will expand and leverage its focus from (1) the agents and resources of scholarly communication to workflows and processes, (2) from publications to data, software, and other research outputs, and the links between them, and (3) strengthen the relationship of European OA infrastructures with other regions of the world, in particular Latin America and the U.S. Through these efforts OpenAIRE2020 will truly support and accelerate Open Science and Scholarship, of which Open Access is of fundamental importance. OpenAIRE2020 continues and extends OpenAIREs scholarly communication infrastructure to manage and monitor the outcomes of EC-funded research. It combines its substantial networking capacities and technical capabilities to deliver a robust infrastructure offering support for the Open Access policies in Horizon 2020, via a range of pan-European outreach activities and a suite of services for key stakeholders. It provides researcher support and services for the Open Data Pilot and investigates its legal ramifications. The project offers to national funders the ability to implement OpenAIRE services to monitor research output, whilst new impact measures for research are investigated. OpenAIRE2020 engages with innovative publishing and data initiatives via studies and pilots. By liaising with global infrastructures, it ensures international interoperability of repositories and their valuable OA contents. To ensure sustainability and long-term health for the overall OpenAIRE infrastructure, the proposed OpenAIRE2020 project will establish itself as a legal entity, which will manage the production-level responsibilities securing 24/7 reliability and continuity to all relevant user groups, data providers and other stakeholders.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: INFRAIA-1-2014-2015 | Award Amount: 13.00M | Year: 2015

Particle physics is at the forefront of the ERA, attracting a global community of more than 10,000 scientists. With the upgrade of the LHC and the preparation of new experiments, the community will have to overcome unprecedented challenges in order to answer fundamental questions concerning the Higgs boson, neutrinos, and physics beyond the Standard Model. Major developments in detector technology are required to ensure the success of these endeavours. The AIDA-2020 project brings together the leading European infrastructures in detector development and a number of academic institutes, thus assembling the necessary expertise for the ambitious programme of work. In total, 19 countries and CERN are involved in this programme, which follows closely the priorities of the European Strategy for Particle Physics. AIDA-2020 aims to advance detector technologies beyond current limits by offering well-equipped test beam and irradiation facilities for testing detector systems under its Transnational Access programme. Common software tools, micro-electronics and data acquisition systems are also provided. This shared high-quality infrastructure will ensure optimal use and coherent development, thus increasing knowledge exchange between European groups and maximising scientific progress. The project also exploits the innovation potential of detector research by engaging with European industry for large-scale production of detector systems and by developing applications outside of particle physics, e.g. for medical imaging. AIDA-2020 will lead to enhanced coordination within the European detector community, leveraging EU and national resources. The project will explore novel detector technologies and will provide the ERA with world-class infrastructure for detector development, benefiting thousands of researchers participating in future particle physics projects, and contributing to maintaining Europes leadership of the field.


Grant
Agency: European Commission | Branch: H2020 | Program: CSA | Phase: EINFRA-6-2014 | Award Amount: 2.00M | Year: 2015

Network of HPC Competence Centres for SMEs


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: EINFRA-1-2014 | Award Amount: 11.14M | Year: 2015

The INDIGO-DataCloud project (INDIGO for short) aims at developing a data/computing platform targeted at scientific communities, deployable on multiple hardware, and provisioned over hybrid (private or public) e-infrastructures. This platform will be built by leading European developers, resource providers, e-infrastructures and scientific communities in order to ensure its successful exploitation and sustainability. All members of the consortium share the common interest in developing advanced middleware to sustain the deployment of service models and user tools to tackle the challenges of the Big Data era. INDIGO will exploit the formidable know-how that was built in Europe along the past ten years of collaborations on scientific computing based on different consolidated and emerging paradigms (HPC, Grid and Cloud). Regarding Cloud computing, both the public and private sectors are already offering IaaS-type Cloud resources. However, numerous areas are of interest to scientific communities where Cloud computing uptake is currently lacking, especially at the PaaS and SaaS levels. The project therefore aims at developing tools and platforms based on open source solutions addressing scientific challenges in the Cloud computing, storage and network areas. INDIGO will allow application development and execution on Cloud and Grid based infrastructures, as well as on HPC clusters. The project will extend existing PaaS solutions, allowing public and private e-infrastructures, including those provided by EGI, EUDAT, PRACE and HelixNebula, to integrate their existing services, make them available through GEANT-compliant federated and distributed AA policies, guaranteeing transparency and trust in the provisioning of such services. INDIGO will also address the development of a flexible and modular presentation layer connected to the expanded PaaS and SaaS frameworks developed by the project and allowing innovative user experiences, also from mobile appliances.


Grant
Agency: European Commission | Branch: H2020 | Program: CSA | Phase: H2020-TWINN-2015 | Award Amount: 999.99K | Year: 2016

Research topics in theoretical physics at Ruer Bokovi Institute (RBI) are broad, from understanding the basic constituents of the Universe, to the study of new materials and complex systems. The research is performed within the Division of Theoretical Physics (DTP), mostly in collaboration with European research institutions. However, the effectiveness and impact is increasingly suffering from a strong limitation of resources, in terms of funding for students, collaboration and dissemination, in addition to the low salaries. In this context, RBI recently made significant efforts to increase its research capabilities in the applied sector, in line with the Smart Specialization Strategy. This is planned through two projects, the major infrastructure project O-ZIP (high priority in the Croatian Operational program for the European Structural Funds) and a recently granted ERA Chair project. Both will impact the theoretical community and call for a rise in its level. RBI-T-WINNING will provide the complementary funding for theoretical physics, with the aim of raising the research profile to that of excellent institutions. This aim will be pursued by supporting strong links with leading European research institutions. Intensive exchange of knowledge and experience will be organized with SISSA, CNRS/University of Paris-Sud Orsay, Ludwig Maximilian University and Niels Bohr Institute, excellent european institutes and altogether cover the investigations within theoretical physics. The set of measures include staff exchanges, training, conferences, summer schools, dissemination and outreach activities for impact on the local community. The project also enables active participation of Croatian researchers in top-level physics research programs, for increasing their experience and visibility. In synergy with other related projects RBI-T-WINNING will maximize the overall impact on the research & innovation potential of Croatia in theoretical physics and overall.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: FETOPEN-1-2014 | Award Amount: 4.19M | Year: 2015

The aim of this proposal is to develop an intelligent biocompatible sensing device which detects complex behavioural changes in ion concentrations. The sensor will use wet NOMFETs, coated Si nanowires, self-conjugated polymers, arrays of photocells, flow of lipids. The level of ions will be measured by monitoring changes in the response function of the system. The high sensitivity of the device will be achieved by ensuring a strong coupling between the environment and the device. The key research challenges will be: accessing the feasibility of the idea to use reservoir computing for sensing complex environmental changes, identifying suitable integration strategies for the components, optimizing the sets of input/output pairs (response functions) and the device components for enhanced sensitivity.

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