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Advertising division: JSC - Jülich Supercomputing Centre
Reference number: 2019-052


The Jülich Supercomputing Centre (JSC) at Forschungszentrum Jülich operates one of the most powerful supercomputer infrastructures for scientific and technical applications in Europe and grants scientists in Germany and Europe access to these resources for their research. The department of Federated Systems and Data at JSC develops software for data analysis, data management and workflow management on distributed data and computer systems. The research group Earth System Data Exploration applies these tools to develop new analysis methods for Earth System data with a focus on Deep Machine Learning.
Specifically, the partners in the research project DeepRain develop new deep learning strategies for improving local scale precipitation forecasts based on data from numerical weather prediction models and radar observations.

Strengthen our team as soon as possible

Postdoctoral fellow to develop Deep Learning Methods for the analysis and forecast of weather data

Your Job:

  • Develop new deep learning concepts to identify and use spatio-temporal patterns in weather data and implementation of these concepts on the supercomputer platforms of JSC
  • Co-operate with DeepRain project partners to achieve improved local-scale predictions of precipitation over Germany
  • Stay abreast of current trends in deep learning topics such as video frame prediction or action recognition
  • Publish your results at leading international conferences and in peer-reviewed journals
  • Support the team members to apply deep learning methods to their research questions and help in their training
  • Assist in the project coordination and acquisition of new research projects subject to your abilities and interests

Your Profile:

  • Doctorate degree from a university with internationally accepted quality standards in computer science, software engineering, mathematics, or a related subject
  • Practical experience with modern machine learning methods (CNN, LSTM, GAN, etc.), documented in your dissertation or peer-reviewed publications
  • Ability and willingness to collaborate with the members of the research group and international colleagues
  • Scientific curiosity towards the application of deep learning techniques to weather-related research questions
  • Interested in the development of new deep learning methods and their practical implementation
  • Experience in software development and programming languages such as Python, C++, or R
  • Knowledge of the UNIX/Linux operating system
  • Ability to present your work at international conferences
  • Very good knowledge of English in written and spoken form

Our Offer:

  • Opportunity to work on interesting research questions with high societal relevance in an open and dedicated team
  • Possibility to develop your academic career and engage in the supervision of master and doctoral students
  • Excellent research and computing infrastructures in one of Europe’s largest research facilities
  • Exciting working environment on an attractive research campus with excellent infrastructure, located between the cities of Cologne, Düsseldorf, and Aachen
  • International and interdisciplinary working atmosphere
  • A comprehensive further training programme
  • Flexible working hours and various opportunities to reconcile work and private life
  • Limited for 3 years with possible longer-term prospects
  • Full-time position with the option of slightly reduced working hours
  • Salary and social benefits in conformity with the provisions of the Collective Agreement for the Civil Service (TVöD)

Forschungszentrum Jülich aims to employ more women in this area and therefore particularly welcomes applications from women.

We also welcome applications from disabled persons.

Additional Information

We look forward to receiving your application, preferably online via our online recruitment system on our career site until 31.03.2019, quoting the above-mentioned reference number.

Questions about the vacancy?
Contact us by mentioning the reference number 2019-052:
Please note that for technical reasons we cannot accept applications via email.