Machine Learning Scientist / Machine Learning Scientistess

Machine Learning Scientist (AI-based Weather Forecasting)

Location: 100%, Locarno, fixed-term

Recent advances in AI-based weather prediction have demonstrated remarkable skill and computational efficiency. However, many current machine-learning weather prediction (MLWP) systems primarily rely on Numerical Weather Prediction (NWP) analyses for initialization and only partially utilize the wealth of available satellite observations. With the advent of the Meteosat Third Generation (MTG), new high-frequency and high-resolution measurements of clouds, moisture, temperature, and lightning activity provide unprecedented opportunities for significantly improving regional forecasts.

Project Background

Within the framework of a Research Fellowship supported by EUMETSAT, we are advancing the integration of geostationary satellite observations into a next-generation regional MLWP system. The project builds on an existing graph-based, stretched-grid regional forecasting model developed at MeteoSwiss and is embedded in the Anemoi framework initiated by ECMWF. The objective is to develop and evaluate novel multi-encoder-decoder architectures capable of ingesting various satellite data streams (e.g., radiances, cloud products, lightning observations, hyperspectral soundings) and integrating them into high-frequency forecasting cycles with lead times ranging from short-range to up to 10 days ahead. This work will be carried out in close collaboration with national and international partners, contributing directly to the future operational exploitation of MTG data.

Job Description

We are looking for a Scientific Programmer / Software Developer to join our motivated and interdisciplinary team.

In this role, you will:

• Develop and implement machine-learning model architectures for the direct ingestion of next-generation satellite data (e.g., MTG FCI, LI, IRS) into state-of-the-art regional forecasting models in Anemoi.
• Contribute to the evolution of a multi-encoder-decoder MLWP framework within the Anemoi ecosystem.
• Train, fine-tune, and evaluate models using large-scale meteorological and satellite datasets.
• Quantify the impact of satellite data on forecast skill across variables and lead times.
• Collaborate closely with scientists, ML researchers, and operational forecasting teams to ensure that forecast outputs meet the needs of diverse users.
• Disseminate results through scientific publications, conference presentations, and exchanges with EUMETSAT and partner institutions.

We value individuals who enjoy solving complex problems, collaborating across disciplines, and contributing to various stages of the workflow as the system matures.

This is a fixed-term contract of 1 year, with the possibility of extension for up to an additional 2 years. The main workplace is located at MeteoSwiss Locarno-Monti with regular visits to Zürich. The amount of remuneration will be in accordance with the salary system of ETH Zürich.

Profile

We welcome applications from candidates with diverse backgrounds who meet most (not necessarily all) of the following criteria:

• PhD in computer science, data science, natural sciences (e.g., physics, meteorology), or a related field. Candidates with an MSc and proven professional experience may also be considered.
• Experience working with satellite data (e.g., geostationary observations, radiances, retrieval products).
• Strong programming skills in Python.
• Experience in machine learning, ideally including deep learning architectures such as graph neural networks, transformers, or spatio-temporal models.
• Experience with high-performance or distributed computing environments.
• Good understanding of meteorological processes and numerical weather prediction.
• Interest in DevOps practices and sustainable software engineering.
• Ability to work independently on research questions while contributing to a collaborative team environment.
• Motivation to work in a diverse, interdisciplinary, and international environment.
• Good communication skills (oral and written) in English and one of the Swiss national languages.

Workplace

The main workplace is based in Locarno, Switzerland, combining an innovative environment with access to modern scientific resources.

We Offer

• Direct involvement in shaping next-generation AI-based weather forecasting systems.
• A unique opportunity to contribute to the operational exploitation of Meteosat Third Generation data.
• Direct involvement in bringing cutting-edge ML research into operational use.
• Close collaboration with European partners, including EUMETSAT, European national weather centers, ECMWF, and the wider Anemoi community.
• Access to modern scientific and ML software stacks, including Python, PyTorch, Xarray, and container technologies on high-performance computing infrastructure.
• A supportive, motivated, and interdisciplinary team within a mission-driven public service organization.
• The opportunity to combine scientific impact, societal relevance, and modern software engineering.

We are committed to providing an equal opportunities work environment for all candidates.

We Value Diversity and Sustainability

In line with our values, we encourage an inclusive culture. We promote equality of opportunity, value diversity, and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Our commitment to sustainability reflects a core value—working towards a climate-neutral future.

Curious? So Are We.

Apply online using the form below. Please include:

• Motivation letter
• CV (including your nationality and a link to your latest thesis and publication record)

Further information can be found at the C2SM and MeteoSwiss websites. Questions regarding the position should be directed to Ulrich Hamann (no applications).

Only applications matching the job profile will be considered.

About ETH Zürich

ETH Zurich is one of the world's leading universities specializing in science and technology. We are renowned for excellent education, cutting-edge fundamental research, and the 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 inspires excellence. Located in the heart of Europe, we forge connections all over the world to develop solutions for today's and tomorrow's global challenges.