Postdoctoral Positions in Climate Modeling and Data Science
We invite applications for several full-time positions at the Postdoc or Senior Postdoc level in the Climate Physics group of Prof. Reto Knutti at the Institute for Atmospheric and Climate Science at ETH Zurich.
We are seeking physical scientists with research experience in coupled global or regional climate models, simplified Earth System models, analysis of model results, or machine learning/data science applied to environmental problems.
Successful participants could contribute to the EU Horizon 2020 project ESM2025, “Earth System Models for the Future”. This stream of work will assess Earth system feedbacks using novel machine-learning detection approaches to efficiently diagnose climate feedback signals from short atmospheric (AMIP) simulations, nudged circulation simulations, coupled (CMIP) simulations and potential new simulations using CESM2. The goal is to evaluate global climate models, quantify potentially nonlinear feedbacks and represent them in reduced complexity carbon-cycle and climate models to study climate targets and policy implications.
The second stream of work will develop high-resolution climate information within the framework of the newly funded SPEED2ZERO initiative of the ETH domain: The goal is to develop the climate data required to quantify the impact of climate change and extremes on the availability of renewable energy resources and biodiversity in Switzerland and Europe. Novel machine learning models enable the emulation of high-dimensional density distributions and can learn from high-resolution climate model simulations to generate new plausible weather patterns at a much lower computational cost. Alternatively, physics-based methods for “boosting” very rare and extreme conditions in dynamical global climate models can provide storylines and quantitative estimates of potential future extreme climate events by re-initializing large ensembles from selected event sets for past, present, and future climates.
The third stream of work relates to specific developments required for the next generation of Swiss climate change scenarios targeted for 2025. These developments include the fusion of observations, reanalyses, operational seasonal forecast, initialized decadal prediction and emission-driven long-term regional and global simulations into seamless climate information covering the past, present and future. Key requirements are a consistent treatment of uncertainty across timescales and reference periods, consideration of model performance, bias and emergent constraints, as well as relevance and accessibility to stakeholders. Additional efforts will focus on improving seamless climate information for extremes.
The above topics intersect and additional similar research directions beyond the three listed project streams are possible and encouraged. Collaborations include the National Weather Service MeteoSwiss, the Swiss Data Science Center SDSC, Prof. Nicolai Meinshausen (statistics and machine learning), various group leaders working on energy and biodiversity at the six institutions of the ETH domain, as well as international partners.
The applicants are expected to contribute to one or more of the respective projects and to take leadership in one of the research fields noted, including the supervision of students. The positions are for two years initially and can be extended subject to performance and availability of funding. The starting date is as soon as possible but can be negotiated.
We offer a dynamic and inspiring research environment, excellent work conditions, supercomputing infrastructure, and a large degree of freedom for successful candidates to bring in their 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.
You must have a PhD in physics, climate sciences, statistics or a related subject, ideally working knowledge of climate models, and experience with shell scripting, Linux operating systems, high-performance computing, or advanced statistics and data analysis frameworks (python, R). Regardless of your background, you 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.
About ETH Zürich
ETH Zurich is one of the world’s leading universities specialising in
science and technology. We are renowned for our excellent education,
cutting-edge fundamental research and direct transfer of new knowledge
into society. Over 30,000 people from more than 120 countries find our
university to be a place that promotes independent thinking and an
environment that inspires excellence. Located in the heart of Europe,
yet forging connections all over the world, we work together to
develop solutions for the global challenges of today and tomorrow.
Curious? So are we.
We look forward to receiving your online application with the following documents:
- Publication list
- Names and contact details of three professional references
Please include a detailed statement of motivation and research ideas and a discussion of how and where your existing and future work would fit into the indicated projects. The application deadline is September 30, but a review of applications will continue until the positions are filled.
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Further information about the Institute for Atmospheric and Climate Science can be found on our website . Questions regarding the positions should be directed to Prof. Reto Knutti, (email@example.com ). Administrative requests should be directed to Barbara Wittneben, (firstname.lastname@example.org ).
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