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Scientific activities / projects

Development of causal inference methods in the field causal Inference and machine learning as part of the EU project XAIDA

Starting date

1 December 2021

Duration of contract

3 years

Remuneration

up to German TVöD 14

Type of employment

Full-time

The "Causal Inference" group at German Aerospace Center’s Institute of Data Science develops theoretical foundations, algorithms, and accessible software tools for causal inference and machine learning and closely works with domain experts, especially in the climate sciences. Causal inference is a challenging and promising research field and its application to domains such as climate science will have a high impact both to advance science and to address topics of critical importance for the society. The core methodological topics include causal inference and causal discovery for spatio-temporal dynamical systems, machine learning, deep learning, and nonlinear time series analysis. But the methods are flexible and open for your ideas!

The position is part of the EU project XAIDA together with several EU partners. The goal is the development of causal inference methods to better understand the causes of extreme events (heat waves, rainfall, etc.) from observational and model data.

Your tasks:

  • Development of theory and methods for causal inference and machine learning
  • Implementation of methods in well-documented software
  • Collaboration in the application of methods in different domains, in particular climate science
  • Publication of results in peer-reviewed journals
  • Presentation of results on national and international conferences

To support your international research experience, the group has a generous travel budget for conferences and extended research stays. Currently, we have collaborators at Imperial College London, Oxford, Carnegie Mellon University, National Center for Atmospheric Research (NCAR), and California Institute of Technology, and more.

Your qualifications:

  • aster in mathematics, theoretical physics, statistics, or theoretical computer science
  • Multiyear experience in independent work on the mathematical description and analysis of highly complex systems and deep knowledge in machine learning, causal inference, statistical methods, or related areas
  • track-record of publications in peer-reviewed journals
  • High social communication skills
  • Fluency in written and oral English
  • PhD in mathematics, theoretical physics, statistics, or theoretical computer science desirable
  • Excellent pogramming skills desirable

Your benefits:

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalleled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (f/m/x). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.

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Technical contact

Dr. Jakob Runge
Institute of Data Science

Phone: +49 3641 30960-112

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Vacancy 60048

HR department Berlin

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DLR site Jena

To location

DLR Institute of Data Science

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