PhD in Conditional Generative Modeling for Climate Data

University of Bern; Bern; Vor Ort; CHF 42.000 - 54.000; Vollzeit

Zusammenfassung

The University of Bern invites applications for a PhD position hosted at the Institute of Mathematical Statistics and Actuarial Science (IMSV) as part of the NCCR CLIM+ programme. The successful candidate will join the Uncertainty Quantification and Spatial Statistics group led by Prof.

David Ginsbourger and contribute to climate risk research. The project focuses on Local Risks: Impacts and Adaptation, including downscaling and debiasing input data for hydrological models, with regular

Qualifikationen

• MSc in statistics or a closely related field with a strong mathematical background.
• Strong programming skills in Python and/or R.
• Knowledge and ideally practical experience of generative machine learning.
• Experience working with large datasets, ideally hydrological, meteorological or climate data.
• Very good oral and written communication skills in English.
• Motivation to work in an interdisciplinary and international environment with a collaborative mindset.

Aufgaben

• Contribute to the Local Risks: Impacts and Adaptation work package of the NCCR CLIM+ programme.
• Collaborate with teams at ETH Zurich, MeteoSwiss, EPFL and University of Bern.
• Develop methods for downscaling and debiasing input data for hydrological models.
• Participate in interdisciplinary meetings, seminars and publications.

Kenntnisse

Python

R

Generative ML

Ausbildung

MSc in statistics

Jobbeschreibung

The University of Bern invites applications for a PhD position hosted at the Institute of Mathematical Statistics and Actuarial Science (IMSV) as part of the NCCR CLIM+ programme. The successful candidate will join the Uncertainty Quantification and Spatial Statistics group led by Prof.

David Ginsbourger and contribute to climate risk research. The project focuses on Local Risks: Impacts and Adaptation, including downscaling and debiasing input data for hydrological models, with regular