Academy of Finland selects promising new Postdoctoral Researchers in natural sciences and engineering

The Academy of Finland’s Research Council for Natural Sciences and Engineering today granted funding for 44 new posts as Postdoctoral Researcher. The funding totals around 11 million euros, and the applicant success rate was 14 per cent.

The international reviewers gave an excellent rating (final rating 6 or 5) to 38 per cent of the applications. Only about one in three of these excellent applications could be funded. In its decisions, the Research Council emphasised the competence of the applicants and the scientific quality of the research projects.

The funded researchers carry out high-quality research and have solid collaboration networks. Reko Leino, the Chair of the Research Council, said: “Creating new generations of researchers is important. With Postdoctoral Researcher funding, the Research Council wants to support promising researchers in embarking on a career in research as early as possible. This year, we were particularly pleased to see that 41 per cent of the funded researchers are women. However, generally speaking, the shortage of female applicants in the STEM sector is very worrying.”

Examples of funded projects

Lukáš Flajšman (Aalto University) conducts research into magnonics, which is an emerging field of magnetism studying the physics of spin waves. Spin waves can effectively carry and process microwave signals. Current telecommunication technology uses bulky microwave processing components as they use microwave radiation with millimetre wavelengths. Magnonics can help scale down microwave processing devices by a factor of 1,000, but this requires the development of basic building blocks of magnonic circuitry. Flajšman’s project combines magnonics and micromechanics for on-chip integration of new device functionalities at room temperature.

Anne Hietava (University of Oulu) investigates how increasing the hydrogen content in blast furnace gas and partially replacing fossil-based carbon with renewable carbon from biomass can affect biocoke and iron-bearing materials. Since the blast-furnace steelmaking route is largely coal-based, the steelmaking industry is responsible for 7 per cent of global anthropogenic CO2 emissions. The amount of steel produced is increasing rapidly – nearly two billion tonnes of steel was produced worldwide in 2019

Razane Tajeddine (University of Helsinki) explores privacy-preserving machine learning. In many cases, the datasets used for machine learning contain sensitive or confidential information. However, it has been noted that commonly used machine-learning methods leak this sensitive information, which limits the use of such methods. Tajeddine’s project will focus on private machine learning on data distributed to multiple parties. The project aims to develop publicly available software that will give third parties the ability to use data without having to access confidential information.