The Data Analytics Group at the University of Mannheim is offering a
Full-Time PhD Position in Machine Learning (TV-L 13)
for 3 years with a possibility of extension of up to 6 years. The Data Analytics Group is a part of the Data and Web Science Group of the university of Mannheim, a joint research group comprising multiple chairs, postdoctoral students, and PhD students. Our research focuses on systems and methods for analyzing and learning from large datasets as well as their applications in practice, with a particular focus on learning with graph-structured data and/
Successful applicants will:
- Conduct cutting-edge research in the field of machine learning and data analysis
- Publish and present research results at internationally renowned venues
- Participate in the teaching activities of the Data Analytics Group (e.g., course tutor or student supervision)
To apply, you should have:
- An MSc degree and strong background in computer science, machine learning, or related fields
- Very good programming skills (esp. Python) and practical experience with machine learning frameworks
- Ability to work independently and goal-driven, both on your own and within a larger team
- Strong analytical thinking skills
- High motivation to conduct research and teach
- Excellent English communication skills (German skills are not required)
The University of Mannheim provides:
- An excellent research environment and intensive collaboration opportunities with researchers from the Data and Web Science group and beyond
- Excellent, flexible working conditions and compute infrastructure
- A full-time PhD position with a competitive salary (TV-L 13)
The position is available from mid August onwards. We welcome applications before or until Aug 15, but the call will remain open for later applications until the position is filled.
To apply, send an e-mail to Kerstin Maier with at least the following information in a single PDF document:
- Short cover letter
- Academic CV
- Transcripts for your BSc and MSc degrees
- Academic writing sample (ideally, your MSc thesis)
For further information and details, please contact Prof. Rainer Gemulla. Additional information is also available on the group's website.