Machine Learning Expert in Climate Science

7 hours ago


Stockholm, Stockholm, Sweden MPOWIR Mentoring Physical Oceanography Women to Increase Retention Full time
Job Overview
MPOWIR Mentoring Physical Oceanography Women to Increase Retention is seeking a highly skilled Postdoctoral Fellow in Machine Learning for Applications in Climate Science. The successful candidate will work on developing machine learning methods for climate studies, meteorology, and oceanography. This is a full-time employment opportunity for a maximum of two years, with the possibility of extension.

About the Project
The project is funded by the Swedish e-science Research Centre (SeRC) and involves collaboration with other scientists in a multidisciplinary project called SeRC Data Science. The successful candidate will interact with researchers from Stockholm University, the Royal Institute of Technology (KTH), Linköping University, and Karolinska Institutet.

Research Opportunities
One possible research project idea involves oceanography and analysis of data from drifting platforms. Machine learning methods could help obtain a more complete picture and deeper understanding of multiscale ocean variability. Another area of focus is uncertainty quantification in measurements from multiple instruments. A methodological approach could involve further development of clustering methods proposed by Koszalka et al. (2011).

Collaboration and Training
The project would be pursued in collaboration with Shane Elipot (RSMAS, University of Miami) and other members of the oceanographic community. Prospective applicants are encouraged to contact the involved scientists prior to applying.

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