19 data "https:" "https:" "https:" "https:" "University of Ostrava" research jobs at AALTO UNIVERSITY in United Kingdom
Sort by
Refine Your Search
-
high in quality of life and was just listed again as the happiest country in the world for the ninth straight year: https://www.worldhappiness.report/ed/2026/ . For more information about living in
-
, carrying out experiments, and data analysis Experience in one of the following fields is highly valued in the choice of the candidate: enzymatic catalysis, cellulose chemistry and characterization, and/or
-
Condition Modelling Are you interested in developing data-driven methods that improve how water utilities understand, manage, and prioritise their buried infrastructure? We are now looking for a Doctoral
-
/ For more information about living in Finland: https://www.aalto.fi/en/careers-at-aalto/living-in-finland & https://www.aalto.fi/en/services/welcome-to-aalto-university-and-finland-info-package . More about
-
happiest country in the world: https://worldhappiness.report/news/its-a-three-peat-finland-keeps-top-spot-as-happiest-country-in-world/ For more information about living in Finland: https://www.aalto.fi/en
-
generations of research and development professionals, data specialists, technology experts, inventors, and scientists for industry and society. The Macroscopic Quantum Optics (MQO) Group and Quantum
-
generations of research and development professionals, data specialists, technology experts, inventors, and scientists for industry and society. The Soft Matter and Wetting Group headed by Prof. Robin Ras
-
information on the available positions, please contact Prof. Tuomas Hytönen and/or Prof. Riikka Korte (riikka.korte@aalto.fi ) . In application process related questions, please contact HR Partner Johanna
-
to the eRecruitment (Workday) system, each 5MB. Contact Information: More information can be found on our website at https://www.hiit.fi/hiit-postdoctoral-fellow-positions-in-computer-science . For questions regarding
-
Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
for sequential data modelling, including Physics-informed Machine Learning and Koopman Operator-based representation framework, towards building interpretable predictive models for complex multi-physics dynamical