Postdoctoral researcher – Downscaling Climate Services; R2

Reference: _ES_ESS_R2

Job title:

Postdoctoral researcher - Downscaling for Climate Services (R2)

The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses Mare Nostrum, one of the most powerful supercomputers in Europe, was a founding member of the former European HPC infrastructure PRACE, and is now the hosting entity for EuroHPC JU, the Joint Undertaking that leads large‑scale investments and HPC provision in Europe.

The mission of BSC is to research, develop and manage information technologies to facilitate scientific progress. BSC combines HPC service provision and R&D in computer and computational science (life, earth and engineering sciences) under one roof, already hosting over 1000 staff from 60 countries.

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We are particularly interested in the strengths and lived experiences of women and under‑represented groups to help us avoid perpetuating biases and oversights in science and IT research. In instances of equal merit, the incorporation of the under‑represented sex will be favoured. We promote Equity, Diversity and Inclusion, fostering an environment where each and every one of us is appreciated for who we are, regardless of our differences.

If you consider that you do not meet all the requirements, we encourage you to continue applying for the job offer. We value diversity of experiences and skills, and you could bring unique perspectives to our team.

The Climate Services (CS) Team within the Earth System Services Group (ESS) is seeking a highly motivated postdoctoral scientist to conduct cutting‑edge methodological research on statistical and machine learning downscaling methodologies for climate predictions at sub‑seasonal to decadal timescales, as well as for climate projections. The mission of the CS Team is to apply state‑of‑the‑art scientific climate knowledge for the co‑development of actionable climate information and solutions relevant for key societal sectors (e.g. agriculture, renewable energy, health) in their adaptation to climate change.

The CS Team is part of the Earth System Services Group (ESS) within the Earth Sciences Department, whose mission is to research the impact of weather, atmospheric chemistry and climate upon socio‑economic sectors, including renewable energy, agriculture, water management, forest fires, urban development and health, and demonstrate the ongoing value of earth system services to society and the economy.

The selected candidate will identify and apply statistical and machine learning downscaling techniques to sub‑seasonal and seasonal predictions, taking into account cross‑timescale differences at regional and local scales to fulfil stakeholders’ needs. This includes developing tailored tools for downscaling to contribute to ongoing projects and services. The candidate will tackle research questions related to improving climate predictions, spatial resolution for decision‑making and their impact on the skill and reliability of climate information.

The candidate will benefit from interdisciplinary training opportunities tailored to their experience and interests. The research will be positioned within the context of WMO’s Global Framework for Climate Services (GFCS), whose aim is to provide actionable climate information to key sectors of society. This position presents an opportunity to work alongside a wide range of leading international climate scientists, informing policy makers across Europe and worldwide.

The position holder will enjoy joining one of the leading and most dynamic European groups in the field of climate services.

Successful candidates will benefit from expert training and BSC‑CNS staff benefits: an international multidisciplinary scientific environment and advanced applied research training. We encourage applications from highly motivated candidates with demonstrated experience in statistical downscaling and AI and a strong interest in applied research in the context of climate services.

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