Postdoctoral Research Fellow

vor 3 Wochen

Karlsruhe, Baden-Württemberg, Deutschland Karlsruher Institut für Technologie Vollzeit

Research Position in Bayesian Statistics and Machine Learning

The Karlsruher Institut für Technologie (KIT) is seeking a highly qualified postdoctoral research fellow to join its Scientific Computing Center. The successful candidate will be part of the newly established Research Group Methods for Big Data and will contribute to the development of novel statistical methods that leverage the potential of Bayesian statistics and machine learning.

The research group focuses on the theoretical and computational aspects of Bayesian statistics, with a strong emphasis on high-dimensional statistics, distributional and advanced regression, survival analysis, variational inference, and copula modeling. The ideal candidate will have a strong track record of publications in these areas and excellent programming skills in scientific programming languages such as Python or R.

The postdoctoral research fellow will be responsible for developing novel statistical methods, investigating their theoretical properties, implementing them, and contributing to joint research inside the group. The successful candidate will also be expected to publish the results at leading journals, workshops, and conferences.

The KIT offers an exciting and varied job within an agile team, as well as a wide range of training opportunities and flexible and family-friendly working time models. If you are a highly motivated and talented researcher with a strong background in Bayesian statistics and machine learning, we encourage you to apply for this position.

Requirements

  • Excellent university degree (master) and completed PhD in statistics, mathematics, data science, or statistics-oriented computer science
  • Strong expertise in the theoretical and computational aspects of Bayesian statistics
  • Profound expertise in at least one of the following areas: high-dimensional statistics, distributional and advanced regression, survival analysis, variational inference, copula modeling
  • Track record and excellent publications in at least one of the main research areas above
  • Strong computational, mathematical skills
  • Solid programming skills in any scientific programming language, e.g. Python, R
  • High proficiency in English, both written and spoken for your scientific publications and presentations
  • High degree of creativity, commitment, analytical competence, and interdisciplinary teamwork

Salary

Salary category 13, depending on the fulfillment of professional and personal requirements.

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