Jacobs University Bremen is an international, private residential university in Bremen, Germany.Jacobs University is an English-speaking higher education institution and combines aspects from the American and German academic systems. Wikipedia.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: INFRAIA-1-2014-2015 | Award Amount: 10.23M | Year: 2015
The Europlanet 2020 Research Infrastructure (EPN2020-RI) will address key scientific and technological challenges facing modern planetary science by providing open access to state-of-the-art research data, models and facilities across the European Research Area. Its Transnational Access activities will provide access to world-leading laboratory facilities that simulate conditions found on planetary bodies as well as specific analogue field sites for Mars, Europa and Titan. Its Virtual Access activities will make available the diverse datasets and visualisation tools needed for comparing and understanding planetary environments in the Solar System and beyond. By providing the underpinning facilities that European planetary scientists need to conduct their research, EPN2020-RI will create cooperation and effective synergies between its different components: space exploration, ground-based observations, laboratory and field experiments, numerical modelling, and technology. EPN2020-RI builds on the foundations of successful FP6 and FP7 Europlanet programmes that established the Europlanet brand and built structures that will be used in the Networking Activities of EPN2020-RI to coordinate the European planetary science communitys research. It will disseminate its results to a wide range of stakeholders including industry, policy makers and, crucially, both the wider public and the next generation of researchers and opinion formers, now in education. As an Advanced Infrastructure we place particular emphasis on widening the participation of previously under-represented research communities and stakeholders. We will include new countries and Inclusiveness Member States, via workshops, team meetings, and personnel exchanges, to broaden/widen/expand and improve the scientific and innovation impact of the infrastructure. EPN2020-RI will therefore build a truly pan-European community that shares common goals, facilities, personnel, data and IP across national boundaries
Agency: Cordis | Branch: H2020 | Program: IA | Phase: BG-04-2014 | Award Amount: 7.40M | Year: 2015
INMARE stands for Industrial Applications of Marine Enzymes: Innovative screening and expression platforms to discover and use the functional protein diversity from the sea. It is a collaborative Innovation Action to streamline the pathways of discovery and industrial applications of new marine enzymes and bioactives for targeted production of fine chemicals, drugs and in environmental clean-up applications. The INMARE consortium will unify the multidisciplinary expertise and facilities of academic and industry partners. This will include integrating the following core activities: advanced technologies to access and sample unique marine biodiversity hot-spots; state-of-the art technologies for construction of metagenomic libraries; innovative enzyme screening assays and platforms; cutting-edge sequence annotation pipelines and bioinformatics resources; high-end activity screening technology; bioanalytical and bioprocess engineering facilities and expertise, nanoparticle-biocatalysts; high-quality protein crystallization and structural analysis facilities and experts in IP management for biotechnology. The companies involved in the project are market leaders in enzyme production and biocatalysis processes designed to efficiently deliver safer (pharmaceuticals) cheaper (agriculture) and biobased (biopolymers) products. They also have impressive track record in environmental clean-up technologies and are committed to promoting public understanding, awareness and dissemination of scientific research. The main emphasis will be focused on streamlining and shortening the pipelines for enzyme and bioactive compound discovery towards industrial applications through the establishing of marine enzyme collections with a high proportion of enzymes-allrounders. The project will also prioritize the identification of novel lead products and the delivery of improved prototypes for new biocatalytic processes.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: INFRADEV-4-2014-2015 | Award Amount: 14.84M | Year: 2015
The social and economic challenges of ageing populations and chronic disease can only be met by translation of biomedical discoveries to new, innovative and cost effective treatments. The ESFRI Biological and Medical Research Infrastructures (BMS RI) underpin every step in this process; effectively joining scientific capabilities and shared services will transform the understanding of biological mechanisms and accelerate its translation into medical care. Biological and medical research that addresses the grand challenges of health and ageing span a broad range of scientific disciplines and user communities. The BMS RIs play a central, facilitating role in this groundbreaking research: inter-disciplinary biomedical and translational research requires resources from multiple research infrastructures such as biobank samples, and resources from multiple research infrastructures such as biobank samples, imaging facilities, molecular screening centres or animal models. Through a user-led approach CORBEL will develop the tools, services and data management required by cutting-edge European research projects: collectively the BMS RIs will establish a sustained foundation of collaborative scientific services for biomedical research in Europe and embed the combined infrastructure capabilities into the scientific workflow of advanced users. Furthermore CORBEL will enable the BMS RIs to support users throughout the execution of a scientific project: from planning and grant applications through to the long-term sustainable management and exploitation of research data. By harmonising user access, unifying data management, creating common ethical and legal services, and offering joint innovation support CORBEL will establish and support a new model for biological and medical research in Europe. The BMS RI joint platform will visibly reduce redundancy and simplify project management and transform the ability of users to deliver advanced, cross-disciplinary research.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: BG-06-2014 | Award Amount: 5.34M | Year: 2015
Underwater operations (e.g. oil industry) are demanding and costly activities for which ROV based setups are often deployed in addition to deep divers contributing to operations risks and costs cutting. However the operation of a ROV requires significant off-shore dedicated manpower such a setup typically requires a crew consisting of: (1) an intendant, (2) an operator, and (3) a navigator. This is a baseline, and extra staffing is often provisioned. Furthermore, customers representatives often wish to be physically present at the off-shore location in order to advise on, or to observe the course of the operations. Associated costs are high. In order to reduce the burden of operations, DexROV will work out more cost effective and time efficient ROV operations, where manned support is in a large extent delocalized onshore (i.e. from a ROV control center), possibly at a large distance from the actual operations - thus with latencies in the communication. As a main strategy to mitigate them, DexROV will develop a real time simulation environment to accommodate operators requests on the onshore side with no delays. The simulated environment will exploit cm accuracy 3D models of the environment built online by the ROV, using data acquired with underwater sensors (3D sonar and vision based). A dedicated cognitive engine will analyse users control requests as done in the simulated environment, and will turn them into primitives that the ROV can execute autonomously in the real environment, despite the communication latencies. Effective user interfaces will be developed for dexterous manipulation, including a double advanced arm and hand force feedback exoskeleton. The ROV will be equipped with a pair of new force sensing capable manipulators and dexterous end-effectors: they will be integrated within a modular skid. The outcomes of the project will be integrated and evaluated in a series of tests and evaluation campaigns, culminating with a realistic offshore trial.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: MG-3.5a-2014 | Award Amount: 6.00M | Year: 2015
Cooperative intelligent transport system (C-ITS) applications rely on knowledge of the geographical positions of vehicles. Unfortunately, satellite-based positioning systems (e.g., GPS and Galileo) are unable to provide sufficiently accurate position information for many important applications and in certain challenging but common environments (e.g., urban canyons and tunnels). This project addresses this problem by combining traditional satellite systems with an innovative use of on-board sensing and infrastructure-based wireless communication technologies (e.g., Wi-Fi, ITS-G5, UWB tracking, Zigbee, Bluetooth, LTE...) to produce advanced, highly-accurate positioning technologies for C-ITS. The results will be integrated into the facilities layer of ETSI C-ITS architecture and will thereby become available for all C-ITS applications, including those targeting the challenging use cases Traffic Safety of Vulnerable Users and Autonomous Driving/platooning. The project will therefore go beyond ego- and infra-structure-based positioning by incorporating them as building blocks to develop an enhanced European-wide positioning service platform based on enhanced Local Dynamic Maps and built on open European standards. Proof-of-concept systems developed in the project will combine infrastructure devices, reference vehicles, communication between road users and offline processing, and will be evaluated under real conditions at TASS test site in Helmond, with the objective of assessing its capabilities to provide high precision positioning to C-ITS applications. When possible, codes and prototypes will be fully open-source and made available to the larger research community as well as to the automotive industry at the end of the project. All achievements will be published in top-tier events further guaranteeing an open-access to all technical publications produced. The project also aims at a strong commitment to bringing the developed solutions to standardization bodies
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: EINFRA-9-2015 | Award Amount: 7.64M | Year: 2015
OpenDreamKit will deliver a flexible toolkit enabling research groups to set up Virtual Research Environments, customised to meet the varied needs of research projects in pure mathematics and applications and supporting the full research life-cycle from exploration, through proof and publication, to archival and sharing of data and code. OpenDreamKit will be built out of a sustainable ecosystem of community-developed open software, databases, and services, including popular tools such as LinBox, MPIR, Sage(sagemath.org), GAP, PariGP, LMFDB, and Singular. We will extend the Jupyter Notebook environment to provide a flexible UI. By improving and unifying existing building blocks, OpenDreamKit will maximise both sustainability and impact, with beneficiaries extending to scientific computing, physics, chemistry, biology and more and including researchers, teachers, and industrial practitioners. We will define a novel component-based VRE architecture and the adapt existing mathematical software, databases, and UI components to work well within it on varied platforms. Interfaces to standard HPC and grid services will be built in. Our architecture will be informed by recent research into the sociology of mathematical collaboration, so as to properly support actual research practice. The ease of set up, adaptability and global impact will be demonstrated in a variety of demonstrator VREs. We will ourselves study the social challenges associated with large-scale open source code development and of publications based on executable documents, to ensure sustainability. OpenDreamKit will be conducted by a Europe-wide demand-steered collaboration, including leading mathematicians, computational researchers, and software developers long track record of delivering innovative open source software solutions for their respective communities. All produced code and tools will be open source.
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: ICT-25-2015 | Award Amount: 4.18M | Year: 2016
We propose to fabricate a chip implementing a neuromorphic architecture that supports state-of-the-art machine learning algorithms and spike-based learning mechanisms. With respect to its physical architecture this chip will feature an ultra low power, scalable and highly configurable neural architecture that will deliver a gain of a factor 50x in power consumption on selected applications compared to conventional digital solutions; and a monolithically integrated 3D technology in Fully-Depleted Silicon on Insulator (FDSOI) at 28nm design rules with integrated Resistive Random Access Memory (RRAM) synaptic elements; We will complete this vision and develop complementary technologies that will allow to address the full spectrum of applications from mobile/autonomous objects to high performance computing coprocessing, by realising (1) a technology to implement on-chip learning, using native adaptive characteristics of electronic synaptic elements; and (2) a scalable platform to interconnect multiple neuromorphic processor chips to build large neural processing systems. The neuromorphic computing system will be developed jointly with advanced neural algorithms and computational architectures for online adaptation, learning, and high-throughput on-line signal processing, delivering 1. an ultra-low power massively parallel non von Neumann computing platform with non-volatile nano-scale devices that support on-line learning mechanisms 2. a programming toolbox of algorithms and data structures tailored to the specific constraints and opportunities of the physical architecture; 3. an array of fundamental application demonstrations instantiating the basic classes of signal processing tasks. The neural chip will validate the concept and be a first step to develop a European technology platform addressing from ultra-low power data processing in autonomous systems (Internet of Things) to energy efficient large data processing in servers and networks.