The Scientific Computing Center is the Information Technology Center of KIT.

The newly established Research Group Methods for Big Data at the Scientific Computing Center welcomes applications for a postdoctoral research fellow (f/m/d).

In this project you will:

• develop novel methods that leverage the potential of statistical learning and Bayesian (Deep) Learning
• investigate the theoretical properties of developed algorithms
• implement the developed methods
• contribute to joint research inside the group
• publish the results at leading journals, workshops and conferences

Details on the research group can be found at https://kleinlab-statml.github.io/

Job requirements:

• Excellent university degree (master) and completed PhD in statistics, mathematics, data science, statistics-oriented computer science
• Strong expertise in theoretical and computational aspects of Bayesian statistics
• Expertise in at least one of the following areas: Statistical Learning, Bayesian (Deep) Learning, Uncertainty Quantification and Probabilistic Machine Learning, High-Dimensional Statistics, Continual Learning
• 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

We offer you 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. For more information about SCC as your new work home, please visit https://www.scc.kit.edu/en/aboutus/working-at-scc.php.

We are looking forward to your application (Motivational letter / CV / Certificates)!

Salary

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