Tampere University gets six new Academy of Finland Postdoctoral Researchers in natural sciences and engineering
The Academy of Finland’s Research Council for Natural Sciences and Engineering has granted funding for 44 new Postdoctoral Researcher posts. Of these funding awards, six were targeted at fields of national and societal importance: energy engineering, medical engineering, process technology, construction engineering, electrical engineering, and computer engineering.
According to Professor Leena Ukkonen, Chair of the Research Council, Postdoctoral Researcher funding was targeted to mobilise high-quality applicants in specific fields. The aim was to encourage talented early-career engineering researchers to pursue academic careers. A further goal was to produce new and high-impact research knowledge on themes that are important for Finnish industry.
The quality of the applications was very high. International reviewers gave an excellent rating of 6 or 5 to 41% per cent of the Postdoctoral Researcher applications, but only a third could be funded. The funding decisions emphasised the applicants’ excellence and the scientific quality of their projects.
The Research Council for Natural Sciences and Engineering allocated about EUR 11 million to the new Postdoctoral Researchers posts. Funding was granted for a three-year period that will begin in September 2022.
A total of 282 applications were submitted, and the success rate was 15.6%. Women received 14% of the funded posts and comprised 23% of the applicants.
Postdoctoral Researcher funding is granted to cover the researcher’s salary and research costs. The researcher is employed at the research organisation that manages the funding.
Artificial intelligence technology for an emerging video coding ecosystem
Alexandre Mercat works in the field of computing sciences at the Faculty of Information Technology and Communication Sciences.
The aim of Mercat’s project is to reconceptualise basic video coding principles by integrating tailored AI-driven decision making into the heart of the video coding process. With novel technologies based on machine learning, he aims to find a solution for three fundamental challenges of video coding: the reduction of encoding complexity, improvement of coding efficiency, and optimising subjective quality. The aim is to make the technologies developed in the project a world-leading academic open-source AI-centric video coding tool.
Agile and Lightweight Learning for On-demand Networks
Olga Vikhrova works in the field of electrical engineering at the Faculty of Information Technology and Communication Sciences.
Vikhrova’s study offers new analysis frameworks and ML-assisted algorithms for the real-time optimising of energy consumption in the wireless network infrastructure. The goal is to make future networks more durable and intelligent.
Novel solutions for improving the overall efficiency of photovoltaic power plants
Kari Lappalainen works in the field of electrical engineering at the Faculty of Information Technology and Communication Sciences.
In his project, Lappalainen aims to develop new solutions for improving the efficiency of photovoltaic power plants by optimal control, sizing, and condition monitoring. The project will provide information and novel methods for optimising the control and operation of photovoltaic power plants. The main research methods include the analysis of high-frequency measurement data which simulates the operations of photovoltaic power plants.
Dynamic, environment-adaptive light-triggered actuators
Hongshuang Guo works in the fields of chemistry and materials science at the Faculty of Engineering and Natural Sciences.
In his project, Guo investigates new methods for developing bioinspired soft robotic materials. The goal of the DELTA project is to build a new materials platform that shows self-adaptation to different environments. DELTA will produce robotic protypes, such as amphibious robots, a reconfigurable micro-gripper, and a cooperating robot team.
Quantum frequency conversion driven by classically non-separable light
Rafael Ferreira Pinto do Rego Barros works in the field of physics at the Faculty of Information Technology and Natural Sciences.
In his project, he investigates the frequency conversion of quantum states driven by classically non-separable vector beams, a novel process that can be termed Hybrid Quantum Frequency Conversion (HQFC). The process will pave a new way for controlling non-linear processes for quantum photonics applications, and it aims at revealing the thin line between classical non-separability and genuine quantum entanglement.
Adaptable integration mechanisms for data-enabled service operations in industrial networks
Khadijeh Mohani works in the field of industrial engineering at the Faculty of Management and Business.
Mohani’s project will offer new insights on the different types of data-enabled service operations, adaptations in business models and alternative approaches to integrate companies in industrial networks. The research will be based on case studies involving machine manufacturers and their customers, stakeholders, and intermediaries.
Read more in the Academy of Finland’s bulletin 12 May 2022.
