PhD Student Position in the project “Meta-Uncertainty in Bayesian Model Comparison“ at University of Stuttgart

The Cluster of Excellence “Data-Integrated Simulation Science” (EXC 2075) is an interdisciplinary research center with more than 200 scientists of different ages, gender identities, nationalities and different subject areas, jointly performing research towards a common goal: We target a new class of modeling and computational methods based on available data from various sources, in order to take the usability, precision and reliability of simulations to a new level. This is why we seek applicants from all parts of society. The open PhD student position is integrated into the Graduate School of the Cluster.

The position is fully paid and part of the project “Meta-Uncertainty in Bayesian Model Comparison” in the Junior-Research Group for Bayesian Statistics of Dr. Paul-Christian Bürkner at the Cluster of Excellence SimTech of the University of Stuttgart.

 

 

Your tasks:

  • Development of statistical methods to quantify (meta-)uncertainty in Bayes model comparison procedures
  • Execution of extensive simulations to evaluate the newly developed methods and compare them to competing approaches
  • Development of software to implement the new methods in open-source programming languages such as R or Python
  • Close cooperation with other scientists within the research group and at the Cluster of Excellence SimTech
  • Publication of research results in international scientific journals and conference proceedings
  • Active participation at national and international conferences

 

Your qualifications:

  • Degree in a field with strong quantitative focus (e.g., mathematics, computer science, biology, or psychology)
  • Strong interest in research questions focused on statistical modelling of complex data
  • Previous experience in applied statistics, mathematical statistics, or machine learning
  • Ideally previous experience in Bayesian statistics
  • Previous experience in at least one programming language common in quantitative fields (e.g., R, Python, Julia, or C++)
  • Previous experience in the probabilistic programming language Stan or another probabilistic programming language is an asset
  • Proficient English skills (spoken and written); German skills are not required
  • High amount of commitment, cognitive flexibility, as well as the ability to work both independently and in a team

 

 

Apply here

Deadline: September 19, 2021

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