Doctoral Researcher / Project Researcher / Research Assistant - fixed-term position in Space Physic
About this role
The Space Research Laboratory (SRL) at the Department of Physics and Astronomy in the University of Turku invites applications for a three-year Project Researcher / Doctoral Researcher / Research Assistant position in space physics. The successful applicant will work in the AIPAD project, which is funded by the Research Council of Finland and is led by Dr. Nina Dresing in collaboration with the Department of Computing of the University of Turku.
AIPAD is a multidisciplinary project that merges spacecraft data with artificial intelligence to solve open questions on the generation of solar energetic particle (SEP) events. Explosive solar eruptions accelerate SEPs to high energies and can cause disruptions of GPS systems and pose serious risks to astronauts. While solar flares and shocks are known to drive these events, their relative contributions to SEP acceleration often remain a puzzle. AIPAD tackles this by developing innovative AI algorithms to fill observational gaps and predict SEP event observables aiming at ultimately revealing the underlying processes of SEP generation.
Job description
The position is hosted at the Department of Physics and Astronomy, Space Research Laboratory (SRL). SRL conducts experimental and numerical work on solar eruptions, in particular on energetic particle eruptions that constitute a radiation threat for manned and unmanned spacecraft in near-Earth space and the interplanetary medium.
The successful candidate will work towards a PhD in space physics under the supervision of Dr. Nina Dresing. The project is a joint collaboration of SRL and the Algorithmics and Computational Intelligence research group at the Department of Computing.
The PhD project focuses on solar energetic particle (SEP) measurements by various space missions. Several instruments allow to measure SEP pitch-angle distributions (PADs) but most of these currently suffer from observation gaps. The goal of the project is to fill these gaps using machine learning m