SMHIs Hydrological Research unit works in Sweden, Europe and worldwide with developing Water and Climate services based on forecast and scenario tools. We assess and predict variability in water resources, climate change impacts, and water quality in catchments including pollutant transport. Our work aims to improve decision-making for water resource management and environmental control, as well as forecasting in early warning services for water-related sectors. We work directly with both external end-users and SMHI’s operational divisions. The unit is very international with some 42 employees from 15 countries.

We are now looking forward to employing a postdoctoral scientist with experience in applying environmental statistical and machine learning (ML) methods for analyzing natural extreme events.

About the position:

You will work with large hydrological and climatological datasets, which you will analyze for extreme events using environmental statistical and ML methods. A focus of your work lies on the interactions between various extremes, particularly high flows, droughts, heatwaves, wildfires, and extreme weather. Additionally, you will have the opportunity to contribute to ongoing ML-based research on hydrological model post-processing using observations, homogenizing input data, and improving hydrological forecasts.

We work in various projects, and you will work in teams of different sizes with each project working towards achieving project-specific goals. The work includes scientific analyses, programming, quality assurance, and documentation. You are expected to publish at least one article in a scientific journal per year.

Your profile:

We are looking for a colleague who is goal-oriented, dedicated, and able to work both independently and collaboratively with others. You have a university degree with a Ph.D. in Earth Sciences, Environmental Statistics, or a related field that SMHI deems equivalent.

We are looking for you with (requirements):

• Experience in geoscientific data and analyses of natural extreme events
• Demonstrated competence in Machine Learning/Artificial Intelligence, e.g., through scientific publication or project participation
• Proficiency in programming (e.g., R, Python) related to handling large datasets and Machine Learning methods
• Proficiency in MS Office
• Excellent English language skills, both verbal and written

Preference will be given to those who have:

• Experience in hydrological modeling and working with hydro-climatological data
• Experience in statistical methods for detecting extreme values and analyzing interactions between different extremes
• Experience in Machine Learning methods for detecting extreme values
• Knowledge of supercomputer environments
• Familiarity with development tools, e.g., git
• Well-developed professional networks

You are familiar with giving presentations and lectures, working in teams, agile approaches and delivering scientific results within defined project goals in a timely and qualitative manner. We work in a multicultural environment where good communication skills are required.

You are research-oriented with published scientific articles and have a scientific work approach with motivation to publish your results.

You already have a permit to live and work in Sweden (e.g. you have an EU citizenship).

Employment: Fixed-term employment for 2 years as a postdoctoral researcher according to the Agreement on limited-term employment valid in Sweden, with a possibility of extension with a total employment period not exceeding three years. We would like you to start in June 2024 or as soon as possible.

Location: Norrköping

Last day to apply: 7 May 2024

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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