Deutscher Wetterdienst
Der Deutsche Wetterdienst ist Teil eines 357.582 km² großen Karrierenetzwerks bestehend aus über 40 Behörden mit rund 24.000 Beschäftigten. Mehr unter www.damit-alles-läuft.de.
The Deutscher Wetterdienst (DWD) is looking for several Early Career Fellows at the ECMWF site in Bonn for a period of 2 years as of January 2025 for the STEP UP! Fellowship programme for early career scientists.
Early Career Fellows (m/w/d)
The DWD awards fellowships to early career scientists to work on a research project during a guest stay at the ECMWF. Fellows will be based at the ECMWF site in Bonn, Germany for a duration of two years.
The European Centre for Medium-Range Weather Forecasts (ECMWF) is an independent international organisation supported by 23 European Member States and 12 cooperating states. It is the world leader in global medium-range forecasts, monthly forecasts and seasonal forecasts. Its products are provided to the European national weather services. The ECMWF site in Bonn was opened in 2021 and employs around 200 scientists, researches, software engineers and other experts.
The Early Career Fellow will work with scientists from different teams within ECMWF. The work will also include support by and collaboration with the Center for Earth System Observation and Computational Analysis (University of Bonn, University of Cologne and Forschungszentrum Jülich).
In addition to the research activities at ECMWF, an important component of the STEP UP! Fellowship programme is a training programme financed by DWD to support the Early Career Fellows' professional and career development during their stay with ECMWF.
The next cohort of Early Career Fellows will apply for following research topics:
Topic 1: Interfacing with Digital Twins
Topic 2: Generative Machine Learning (ML)
Topic 3: Investigate GNSS-R observation usage over land surface
Topic 4: Discerning the effect of the Land Data Assimilation System (LDAS) on flood forecasting
Topic 5: Using observations to improve cloud and precipitation processes for numerical weather prediction
It is possible to apply for several topics. Please indicate in your application which project(s) you are applying for (including a ranking).
Please find more information on the tasks of the individual research topics, the possibility of an extension as part of a PhD and the programme in general here:
https://www.dwd.de/DE/derdwd/arbeitgeber/einsteigen/fellowship/fellowship.html?nn=20138
Your profile:
Further Qualifications:
Desirable competences and skills:
Topic 1: Experience or expertise in numerical modelling of physical processes.
Knowledge of shell scripts and python and being able to read/understand (Fortran) code.
Background in global or regional simulations is desirable.
Topic 2: Experience is required in training generative machine learning models applied to images/videos or similar application.
Experience developing generative models is advantageous.
Strong Python skills (or similar language) are required.
Topic 3: Expertise in land surface data assimilation and radiative transfer modelling.
Experience in handling Earth observation datasets.
Strong programming skills, ideally in Python, Fortran, and UNIX shell scripting or equivalent.
Topic 4: Expertise in land data assimilation, land surface modelling and/or hydrological data analysis is desirable.
Expertise in numerical modelling and/or data assimilation is an advantage.
Background in global or regional simulations with weather or climate models is desirable.
Topic 5: Meteorology background with experience in cloud physics, remote sensing or radiative transfer is desirable.
Good programming and statistical analysis skills.
Experience in evaluating models with observations, statistical analysis and handling large datasets is desirable.
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