Marie Sklodowska-Curie networks
Two ITN projects that are coordinated by TUT are currently in progress at the University. Innovative Training Networks (ITN) provide training and research experience to early-stage researchers.
BigDataFinance, Coordinator Juho Kanniainen
BigDataFinance provides the European financial community with specialists with state-of-the-art skills in finance and data-analysis to facilitate the adoption of reliable and realistic methods in the industry. This increases the financial strength of banks and other financial institutions in Europe.
ETN-FPI, Coordinator Atanas Gotchev
The research concept of the network is to depart from the notations of plenoptics, light field and integral imaging, used sometimes interchangeably, and to harmonize and advance further the research in these areas under the umbrella of the wider and viewer-centred FPI concept. The training disciplines include theoretical and applied optics, multi-dimensional image processing, and visual neuroscience.
In addition, TUT is engaged as a partner in the following projects:
MacSeNet will go beyond the current, and hugely popular, sparse representation and compressed sensing approaches, to develop new signal models and sensing paradigms. These will include those based on new structures, nonlinear models, and physical models, while at the same time finding computationally efficient methods to perform this processing.
ABWET (European Joint Doctorate)
ABWET is centred around environmental technologies for treatment of waste, with a focus on anaerobic treatment processes, valorisation of the digestate and biofuel clean-up. ABWET focuses on fundamental and applied research of different treatment technologies as well as on the development of innovative recovery and reuse technologies with enhanced market potential. A strong industrial participation will bring a close connection to practical problems.
PURESAFE, Coordinator Jouni Mattila
The PURESAFE network answers to the increasing need of skilled and well trained researchers possessing a holistic system understanding of scientific and energy generation facilities. The trained researchers receive excellent career prospects on demanding RTD of scientific facilities, knowledge intensive products and services including RTD and decommissioning of nuclear power plants in growing markets."
CONTACT , TUT as a partner
18 researchers, in unique collaboration with cutting-edge teams, will work to overcome recognised limitations in the state of the art, including the adjustment of CNT surface properties, CNT dispersion in thermosets and thermoplastics, reliable analysis and characterisation. Carefully structured networking will ensure the efficient exchange of knowledge between researchers, the partners and society. Focus on 3 specific end-use applications (construction, wind blades, electrodes) will ensure quantifiable and tangible results
HPCFinance, Coordinator Juho Kanniainen
HPCFinance, a training network in modern quantitative methods and High-Performance Computing for Finance, provides solutions to managing financial risks by high-performance computing. HPCFinance will help improve the financial strength of banks, pension funds, insurance companies, other financial institutions and households in Europe
MULTI-POS, Coordinator Jari Nurmi
MULTI-POS will bridge the gap between the lower technology layer and upper application layer involved in wireless mobile location. In addition, MULTI-POS will offer comprehensive training to young fellows in the broad field of wireless location, will create novel technologies and business models for the future location-enabled wireless devices, will promote the exchange of fellows in mixed academic-industrial R&D trajectories and in multiple European cultures, and will initiate an educational and research framework that unifies the currently fragmented research activities on technological and applications aspects of wireless navigation.
INSPIRE will create a permanent collection of measurement data and tools that are accessible for external researchers for testing and comparing speech intelligibility models, thus enabling a breakthrough improvement in hearing instrument tuning.