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. We are taking part to a Marie Skłodowska-Curie Doctoral Network project “Advancing Energy Conversion Technologies: High-Frequency Magnetics in Modern Power Electronics” (MAGNIFY). The project is a
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used in analysing drivers of species communities and to make predictions to non-explored areas. In this project, these models will be extended to predict ecosystem functions (e.g., total biomass
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disease, found both in tropical and temperate regions. The laboratory aims to establish a comprehensive view of host interaction during alphavirus replication by identifying host proteins that assist in
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host interaction during alphavirus replication by identifying host proteins that assist in virus replication. We aim to understand the specific actions that each host factor performs during virus
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public events and assisting with research projects. Please send your application to riikka.rossi@helsinki.fi by October 20th, 2025 a cover letter stating your motivation to apply for the position and your
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Council of Finland funded research project ‘Manicuring Intimacy: Feminised labour, (self-)care, and racialised encounters in nail salons’ (INTIMATE, 2025-2029). The position starts 1.1.2026 or as agreed and
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learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted drug design” is led by Docent Juri Timonen
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oxygenates production. In this project, we particularly aim green methanol production in the context of circular economy. The research activities in this doctoral thesis are planned with the view of developing
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Grant, focusing on the development of novel deep learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted
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stability theory, modeling & identification, optimal control, certifiably safe & robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven