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Postdoc position: Statistical Data Science and Machine Learning for Climate Change Research 80-100%, 2 years (possibility 1 year extension), Bern
UniBE is ambitious.
With us, you deliver top performance and test your skills against the best.
What you can expect
Together with the platform leads and members, the recruited person will actively engage in platform coordination and scientific animation activities, provide expertise and feedback to graduate students and other Early Career Researchers. Scientific animation may include crash-courses on topics relevant to the platform and the recruited person. With a baseline affiliation in statistics, the recruited person will be encouraged to regularly visit and possibly be hosted (part time) in other OCCR groups depending on collaborations.
Employment conditions and remuneration are in accordance with the standards of the University of Bern, Switzerland.
The University of Bern is committed to promoting equal opportunities and equality between women and men and all genders, strives to reduce barriers to entry and promotes the reconciliation of work and care responsibilities. For the university, the diverse perspectives of university members are an essential component of excellence in research, teaching and administration.
Profile of the candidate
The successful candidate holds a PhD in statistics / ML / applied mathematics and has a strong interest in climate and weather applications, or he/she holds a PhD in climate or atmospheric science, meteorology or similar with an excellent background in statistics and ML. She/he has excellent programming and data handling skills, and a keen interest in interdisciplinary research. The candidate is proficient in English, both written and spoken.
International reputation
Application and Contact
Evaluation of applications will continue until the position is filled. Please send a single pdf including your CV, motivation letter, a short (max 4 pages) proposal emphasizing the methodological research directions you envision (ideally echoing the broader topic of generative models as decoders for climate foundation models) and how they relate to the one or several OCCR groups from the platform, as well as contact information of 3 references to <a href="mailto:office.stat@unibe.ch" rel="nofollow noopener" target="_blank">office.stat@unibe.ch</a>
Postdoc position: Statistical Data Science and Machine Learning for Climate Change Research
UniBE is ambitious.
With us, you deliver top performance and test your skills against the best.
Start Date
February 1, 2027, or upon agreement
Employment Relationship
80-100%, 2 years (possibility 1 year extension)
Institution / Workplace
Institute of Mathematical Statistics and Actuarial Science and Oeschger Centre for Climate Change Research (OCCR) Bern
About The Project
We are seeking a highly motivated and skilled individual to join the Statistical Data Science and Machine Learning Platform lead by Prof. Dr. David Ginsbourger (Institute of Mathematical Statistics and Actuarial Science) and Prof. Dr. Olivia Romppainen-Martius (Climate Impacts groups, Institute of Geography) in the framework of the Oeschger Centre for Climate Change Research (OCCR). Of particular interest are developments in generative modelling, operator learning, amortized inference, and how recent advances in scientific ML can be leveraged in climate change research, e.g., by combining foundation models with diffusion models for local/specific downstream tasks. Application domains encompass climatology, meteorology, hydrology, and societal aspects of climate change research.
What You Can Expect
Together with the platform leads and members, the recruited person will actively engage in platform coordination and scientific animation activities, provide expertise and feedback to graduate students and other Early Career Researchers. Scientific animation may include crash-courses on topics relevant to the platform and the recruited person. With a baseline affiliation in statistics, the recruited person will be encouraged to regularly visit and possibly be hosted (part time) in other OCCR groups depending on collaborations.
Employment conditions and remuneration are in accordance with the standards of the University of Bern, Switzerland.
The University of Bern is committed to promoting equal opportunities and equality between women and men and all genders, strives to reduce barriers to entry and promotes the reconciliation of work and care responsibilities. For the university, the diverse perspectives of university members are an essential component of excellence in research, teaching and administration.
Profile of the candidate
The successful candidate holds a PhD in statistics / ML / applied mathematics and has a strong interest in climate and weather applications, or he/she holds a PhD in climate or atmospheric science, meteorology or similar with an excellent background in statistics and ML. She/he has excellent programming and data handling skills, and a keen interest in interdisciplinary research. The candidate is proficient in English, both written and spoken.
More Information
Job-Abo
Application Process
Your Benefits
International reputation
Strong research infrastructure and international network
Collaborative environment and ambitious team
Individual career support
Other Benefits
Your Benefits
<ul>
<li>International reputation</li>
<li>Strong research infrastructure and international network</li>
<li>Collaborative environment and ambitious team</li>
<li>Individual career support</li>
</ul>
Working at the University of Bern
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Application and Contact
Evaluation of applications will continue until the position is filled. Please send a single pdf including your CV, motivation letter, a short (max 4 pages) proposal emphasizing the methodological research directions you envision (ideally echoing the broader topic of generative models as decoders for climate foundation models) and how they relate to the one or several OCCR groups from the platform, as well as contact information of 3 references to <a href="mailto:office.stat@unibe.ch" rel="nofollow noopener" target="_blank">office.stat@unibe.ch</a>
Questions about the position?
Prof. Dr. David Ginsbourger (<a href="mailto:david.ginsbourger@unibe.ch" rel="nofollow noopener" target="_blank">david.ginsbourger@unibe.ch</a>) and Prof. Dr. Olivia Romppainen-Martius (<a href="mailto:olivia.romppainen@unibe.ch" rel="nofollow noopener" target="_blank">olivia.romppainen@unibe.ch</a>)
Questions about the application?
Prof. Dr. David Ginsbourger (<a href="mailto:david.ginsbourger@unibe.ch" rel="nofollow noopener" target="_blank">david.ginsbourger@unibe.ch</a>) and Prof. Dr. Olivia Romppainen-Martius (<a href="mailto:olivia.romppainen@unibe.ch" rel="nofollow noopener" target="_blank">olivia.romppainen@unibe.ch</a>)
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Postdoc position: Statistical Data Science and Machine Learning for Climate Change Research

Postdoc position: Statistical Data Science and Machine Learning for Climate Change Research

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