|From||"Knutti Reto" <email@example.com>|
|Date||Fri, 17 Nov 2017 15:19:19 +0000|
Postdoctoral Fellow in Climate Modeling/Attribution of changes in the water cycle using Big Data, ETH Zurich
We invite applications for a full time position on the Postdoc/Senior Postdoc level jointly between the Climate Physics group of Prof. Reto Knutti at the Institute for Atmospheric and Climate Science, and the Statistics group of Prof. Nicolai Meinshausen at the Seminar for Statistics, both at ETH Zurich.
We are seeking a physical scientist or statistician with research experience in analyzing data from climate models, observations and/or similar datasets. The position is funded by “DAta Science-informed attribution of changes in the Hydrologic cycle (DASH)”, a project of the newly founded Swiss Data Science Center (SDSC). It targets detection and attribution of climate change and aims to combine expertise in climate modeling in the group of Prof. Reto Knutti with that of applied statistics (machine learning, high-dimensional inference, and causality) in the group of Prof. Nicolai Meinshausen. Detection and attribution has been limited by the amount and quality of observations. The availability of more and different types of data offers opportunities to apply Data Science methods to attribution of climate change. Specifically, the goals of this project are to use patterns from models to fill data-sparse regions, filter out unreliable observational data, combine data from different types of models and from different variables, and use advanced statistical methods from the areas of machine learning and causal inference that go beyond simple regression and hypothesis testing.
The applicant is expected to contribute to the respective project and to take leadership in one of the research fields noted, including the supervision of students. The position is for two years initially and can be extended subject to performance and availability of funding. The starting date is as soon as possible, with some flexibility into spring 2018.
Applicants must have a PhD in physics, climate sciences, statistics or related subjects, ideally working knowledge of climate models, and experience with Fortran, shell scripting, UNIX/Linux operating systems, high performance computing, advanced statistics and data analysis systems (such as NCL, python, R, etc.). Regardless of background, the successful applicant will have an interactive personality, motivation to work with cutting-edge numerical climate models and their output, the ability to carry out research in an interdisciplinary and international environment, and a strong desire to disseminate results in conference talks and journal articles. Fluency in English (written and spoken) and strong communication skills, in particular experience in the publication of research results in peer-reviewed journals, is required.
We offer a dynamic and inspiring research environment, excellent work conditions, supercomputing infrastructure, and a large degree of freedom for the successful candidate to bring in her/his own research ideas and experience. The Institute for Atmospheric and Climate Science at ETH Zurich is a world-leading institute in the field of research on global and regional climate change at one of the leading international universities for natural sciences and technology.
We look forward to receiving your online application including a CV, publication list, statement of motivation and research interest and how those would fit into the group and project, names and contact details of three professional references, and electronic versions of the most important publication. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered. Review of applications will continue until the position is filled.
For further information about the Institute for Atmospheric and Climate Science please visit our website www.iac.ethz.ch. Questions regarding the position should be directed to Prof. Reto Knutti by e-mail.
Reto Knutti, ETH Zurich
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