15% of Postdoctoral Researcher applicants in natural sciences and engineering granted funding

12 May 2020

The Academy of Finland’s Research Council for Natural Sciences and Engineering today decided on funding for 43 new posts as Postdoctoral Researcher. The funding totals around 11 million euros, and the success rate was around 15 per cent. Women account for some 28 per cent of the funding recipients and for 30 per cent of the applicants.

International peer reviewers rated 41 per cent of the applications as excellent. The Research Council was able to fund only about one in three of these. In the funding decisions, the Research Council emphasised the importance of the applicant’s qualifications and the high scientific quality of the research.

Professor Reko Leino, Chair of the Research Council, said: “It was nice to note from the applications that, as a rule, natural sciences and engineering researchers are well networked already in the early stages of their careers and cooperate with top researchers in their field.”

The research is often multidisciplinary and carried out in international cooperation. Some of the funded researchers also cooperate with business and industry and are planning research periods of varying lengths in companies or private research institutes. Leino added: “This was the second time that the Research Council encouraged researchers to interact with various societal actors. Stakeholder interaction is particularly important in our sectors.”

The new Postdoctoral Researchers funded by the Research Council for Natural Sciences and Engineering will focus on a broad range of research topics of scientific and societal significance.

Examples of funded researchers

Tatiana Bubba from the University of Helsinki aims to develop new mathematical models and novel algorithms based on the regularisation and optimisation theory in applied mathematics. The problems under investigation have potential applications in two societally significant areas: mammography screening and nuclear weapon safeguards. Bubba’s project is aimed at making leaps in the theoretical and computational methods for two non-linear tomographic problems: imaging of spent nuclear fuels with passive gamma emission tomography and spectral tomography for breast imaging.

Thomas Hausmaninger from VTT Technical Research Centre of Finland Ltd aims to develop a method capable of detecting gases at unprecedented low concentrations. Trace gases are present at very low concentrations in gaseous samples such as atmospheric samples, human exhaled breath or power-plant emissions. Their concentrations are an image of the processes contributing to the gas sample. The higher the resolution of a trace gas detector, the better the processes can be studied. The method to be developed will allow in-situ trace-gas detection in demanding applications for fields such as breath analysis, radioactive leak detection, combustion diagnostics and radio-carbon dating. High-resolution, real-time detection will enable scientists to make significantly more detailed studies in these fields, for example through improved sensing of greenhouse gas sources, or develop applications such as real-time monitoring of nuclear waste handling where fast detection of leaks can prevent catastrophes.

Tuomas Rossi from Aalto University studies plasmonic nanocatalysts. They are metal nanoparticles that enable direct solar-to-chemical energy conversion. Metal nanoparticles are efficient solar energy harvesters thanks to so-called plasmon excitation. The subsequent plasmon decay results in high-energy hot electrons and holes that can trigger chemical reactions on molecules adsorbed on the nanoparticle. Rossi aims to develop computational methods for identifying and optimising atomic-scale features that maximize the plasmonic-catalytic performance of nanostructures. The comprehensive data will be used to obtain fundamental atomic-scale understanding of plasmonic-catalytic processes and to derive atomic-scale material design principles for nanostructures for converting carbon dioxide to reusable compounds for renewable energy.

Ville-Valtteri Visuri from the University of Oulu focuses on electric arc furnace steelmaking. The carbon dioxide emissions of steel produced from scrap using an electric arc furnace are much lower than those of steel produced from iron ore using a blast furnace–converter route. However, the high electricity consumption of the electric arc furnace process needs to be reduced to avoid carbon dioxide emissions associated with electricity production. The prediction of the electric arc furnace process is conducted with mathematical models. However, contemporary models typically do not adapt to changes in process practice and are not applicable for real-time prediction of the process. Visuri aims to develop a model that automatically adapts to plant data, is capable for online modelling and makes use of new online measurements.

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