Are you enthusiastic about meteorology, committed to societal benefit, and eager to continually expand your expertise through the application of cutting-edge scientific methodologies? If so, a position within our development teams is tailor-made for you.

The "Model and System" unit at SMHI oversees the operational models and various systems encompassing meteorology, oceanography, hydrology, satellite, and radar. The outcomes of these computations form the backbone of our forecasting and warning activities. Our computational arsenal ranges from standard PC machines to Linux clusters housed at the NSC supercomputer center in Linköping. We apply diverse scientific methodologies, including Artificial Intelligence (AI).

Within this unit, the "Method" group is responsible for scientific methodology. Presently comprising 8 dedicated members, we are seeking 1-3 additional scientists or engineers to bolster our ranks.

Position Overview:

Your primary focus will be enhancing our operational meteorological forecast products and warnings through physical and statistical post-processing, as well as nowcasting. This entails devising novel models and methodologies, refining existing ones, and contributing to the programming of scientific methods.

You will be integrated into one of our development teams, tasked with processing forecast data sourced from numerical models and various observation systems, including radar, satellite, and weather stations. While our development primarily caters to internal needs, our data and products are also utilized externally. All servers housing our tools and programs run on Linux. Operational system configurations are collaboratively established with system developers within the team. We adopt an agile working approach, ensuring that priorities align closely with the needs of our internal users.

The role may involve participating in our standby duty approximately every 7 weeks or contributing as a meteorological forecaster. Occasional travel, both domestic and international, may be required.

Your Profile:

We seek individuals with a completed university education in natural sciences or civil engineering with a natural science orientation. Alternatively, candidates may possess a background in other mathematical/computer science disciplines, coupled with programming and natural sciences components.

In addition to the above qualifications, you are required to have:

• Proficient programming skills, especially in Python.
• Familiarity with the Linux environment.
• Knowledge of statistical methods for data processing, including statistical post-processing, data assimilation, or machine learning.

Preferred qualifications include:

• Training or experience in machine learning methods.
• Proficiency in low-level languages such as C, C++, and Rust.
• Experience developing code in larger teams (>3) with a strong emphasis on repository usage, e.g., Git.
• Experience handling large datasets.
• Familiarity with weather and climate data, encompassing both modeling and observational aspects.
• Application of machine learning in research or business contexts.
• Experience applying machine learning to address societal challenges.
• Involvement in international collaborations.

You should be performance-oriented, self-motivated, and well-organized. Collaboration should be second nature to you, and you should possess strong analytical problem-solving skills. We value individuals who are driven by the prospect of addressing societal issues and actively engage in dialogue and cooperation with users.

Proficiency in English, both spoken and written, is essential. Candidates lacking proficiency in the Swedish language at the time of employment must achieve at least level B2 according to the European language scale within one year.

Form of employment

 Permanent, full-time position

Location

 At SMHIs main office in Norrköping

Application deadline

Welcome with your application already today, but no later than May 26 2004.

SMHI is an expert authority with a global outlook and a vital mission to forecast changes in weather, water and climate. With a scientific foundation, we use knowledge, research and services to contribute to a more sustainable society. Every hour of every day, all year round.

SMHI is an Agency with a specific responsibility for civil preparedness. Therefore you could be appointed to be mobilised to SMHI for wartime posting.

Bear in mind that all the documentation and information you send to SMHI in conjunction with your application will be classified as public documents. This means that all the material contained in your application, including attachments, may be disclosed if so requested by a party, on the condition that the information is not subject to confidentiality in accordance with the Public Access to Information and Secrecy Act. You should therefore primarily provide such information that you deem to be relevant in relation to the requirements of the position. Think about your own personal privacy, and avoid sharing information that contains sensitive personal data, or information about your health or that of a family member, your political views or religious beliefs.

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