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Early Career Fellows (m/w/d)

Early Career Fellows (m/w/d)

Early Career Fellows (m/w/d)

Early Career Fellows (m/w/d)

BAV Dienstsitz Aurich

Öffentliche Verwaltung

Bonn

  • Art der Beschäftigung: Vollzeit
  • 46.500 € – 60.000 € (von XING geschätzt)
  • Vor Ort
  • Zu den Ersten gehören

Early Career Fellows (m/w/d)

Über diesen Job

The Deutscher Wetterdienst (DWD) is looking for several Early Career Fellows for the "STEP UP! Fellowship programme for early career scientists” at the ECMWF site in Bonn, starting January 2027, for a fixed term of 2 years.

Early Career Fellows (m/w/d)

Reference code 20260571_9300

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 organization 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 houses the EU activities of the ECMWF.

The Early Career Fellows 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.

What we are looking for:

The following research topics of the Fellowship programme are available for application:

  1. Next-Generation Subseasonal-to-Seasonal Forecasting with AI

  2. Improving convection in weather prediction by integrating physical and AI-based approaches

  3. Globally distributed optimisation of ECMWF’s land surface model (ecLand)

  4. Quantifying Observation Impact Across Physical and AI-Based Forecasting Systems

It is possible to apply for multiple topics. Please indicate in your application which project(s) you are applying for (including a ranking).

Please find more information onthe tasks of the individual research topics, the possibility of an extension of the program as part of a PhD and the programme in general here: www.dwd.de/fellowship-eng (http://www.dwd.de/fellowship-eng)

Your profile:

Required Qualifications:

  • · Successfully completed scientific or technical university degree (Bachelor, Master, Diploma), preferably in physics, mathematics, computer science, machine learning, environmental sciences, hydrology, oceanography or meteorology
  • · Confident knowledge of the English language, both spoken and written (at least level B2 CEFR)

Desirable competencies & skills:

Topic 1:

  • Strong foundational knowledge in machine learning and atmospheric science
  • Basic understanding of weather and climate predictability and predictions
  • Experience with Python-based scientific workflows and large geophysical datasets

Topic 2:

  • Strong foundational knowledge in machine learning and atmospheric science
  • Experience in handling large datasets with Python-based scientific workflows is desirable
  • Meteorology background with experience in physical modelling of convection is an advantage

Topic 3:

  • Experience with physical land surface models, parameter optimisation, Earth observation, and data analytics of large datasets in Python is desirable
  • Background in global or regional weather or climate simulations is an advantage
  • Expertise in statistical methods and machine learning is an advantage

Topic 4:

  • Experience in evaluating models with earth observations, statistical analysis and handling large datasets is desirable
  • Expertise in numerical modelling, data assimilation, and machine learning is an advantage
  • Foundational knowledge of Earth Observations, machine learning, and data analytics in Python is desirable

In addition, you bring the following knowledge and skills:

  • Some knowledge of the German language, both spoken and written (Level A2 CEFR), is an advantage
  • Excellent communication and information skills to create a sustainably positive and trusting atmosphere in interactions with people
  • Ability to work constructively and collegially
  • Independence and initiative in solving problems appropriately within one's own field of activity
  • Ability to think and make judgments, to weigh up various familiar factors and form an appropriate judgment
  • Empathy, in order to recognize the different needs of those involved in working in groups and to be able to take these needs into account appropriately
  • Planning and organizational skills with the ability to distinguish between urgent and important tasks over a short period of time
  • Intercultural competence as a prerequisite for successful collaboration in international teams and organizations
  • Experience in cooperation with international organizations is an advantage

What we offer:

The fellowship will amount to a net allowance of 2.900 Euro/month for two years plus individual expenses for travels and costs for publications in accordance to the funding principles.

There is no insurance in the statutory social security system. Corresponding voluntary or private insurance policies must be taken out at the start of the fellowship.

The DWD considers itself a family-friendly employer and has been certified accordingly. You can find further information at www.beruf-und-familie.de (http://www.beruf-und-familie.de)

Special Notes:

The application period ends on May 04, 2026. The fellowship assignments will start in January 2027.

We value diversity and welcome all applications - regardless of age, gender or gender identity, nationality, ethnicity and culture, religion/belief, disability or sexual orientation.

**Nationals of ECMWF member states and cooperating states, as well as all EU member states, are eligible to apply. **ECMWF member and cooperating states are (as of 2026): Austria, Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Georgia, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Latvia, Lithuania, Luxembourg, Montenegro, Morocco, the Netherlands, Norway, North Macedonia, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Türkiye and the United Kingdom.

There is no legal entitlement to the fellowship.

Basis for awarding the fellowship are the funding principles of the STEP UP! Fellowship programme, which are also part of the fellowship agreement.

Applicants are selected through a structured interview (virtual) conducted by an interview panel consisting of ECMWF, CESOC and DWD in English language.

Are you interested?

Please apply, stating your preferred research topic (including a ranking if interested in multiple topics) by May 04, 2026 via the electronic application procedure (EBV) http://www.bav.bund.de/Einstieg-EBV (http://www.bav.bund.de/Einstieg-EBV)

Please enter the above reference code.

Please upload your complete application documents (Letter of motivation, curriculum vitae, Master's/Bachelor's certificate indicating finale grade, internship/work certificates, list of publications if applicable) as an attachment to your candidate profile.

If your documents are not in German or English, please attach an officially certified translation in German or English.

In addition, please enter your degree indicating your final grade in your candidate profile under "Education/Degree" and your language skills under "Languages".

If you have any questions regarding the electronic application procedure, please contact the Federal Institute for Administrative Services at +49 (0)4941 602-240 (mainly German speaking).

Contact person:

For further information, please contact Vanessa Jacobi, tel. +49 (0)69 8062-2822, and Luisa Nottarp, tel. +49 (0)69 8062-3596, at Deutscher Wetterdienst.

Bereitgestellt in Kooperation mit der Bundesagentur für Arbeit.

Gehalts-Prognose

Unternehmens-Details

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BAV Dienstsitz Aurich

Öffentliche Verwaltung

Raunheim, Deutschland

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