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activity using fully compressible MHD in global and local frameworks, integrated with physics‑informed machine learning and coronal/wind modelling. Key tasks and responsibilities: Develop and implement data
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). These are Bayesian dynamical models that combine known mechanistic components with flexible Gaussian process terms representing unknown or misspecified biology. Depending on the candidate’s interests, there may also
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([email protected] ) or Senior University Lecturer Leena Lankoski ([email protected] ). In questions related to the recruitment process, please contact HR Partner Jenna Knuutinen, jenna.knuutinen
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. Demonstrated interest in the physics of sea ice and computational modelling of ice will be considered as an advantage. Suitable backgrounds include solid mechanics, mechanical engineering, computational
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bio-based catalysts. You will have the opportunity to share your results within the vibrant international green chemistry research community, and widen your skills in organic and physical chemistry
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://www.aalto.fi/en/tenure-track/interested-in-joining-our-tenure-track . About recruitment process Only applications submitted through Workday will be considered. We will start the evaluation process in the end
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more information, please contact: Innovation Advisor Pekka Kettunen, [email protected] or by phone +358 50 594 7050. In any question regarding the recruitment process, please contact HR Advisor
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The deadline for applications is October 4th, 2026 at 11:59 PM (23:59 UTC+03:00). Review timeline We ask that all candidates that will continue the recruitment process to provide a public talk. We will contact
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23 Jul 2026 Job Information Organisation/Company AALTO UNIVERSITY Research Field Physics Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application Deadline 14 Aug 2026
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backgrounds to join our community. At the Department of Applied Physics, our pioneering research in physical sciences creates important industrial applications that hold great technological potential. Our