the Institute of Mathematical Stochastics at  TU Dresden invites applications for a 3-year PhD position (extension  possible) to be filled as soon as possible. The position is  within the German AI competence center ScaDS.AI Dresden/Leipzig  (Center for Scalable Data Analytics and Artificial Intelligence).

The successful candidate will take part in  research in the following areas: geometric methods and representations in machine learning, in particular with focus on hyperbolic geometry, embedding methods for graphs  and networks, supervised learning in non-Euclidean settings, embedding and learning for data under hierarchical and relational constraints, theoretical  guarantees and error bounds for geometric embedding methods, prediction and inference of contagion and diffusion processes in non-Euclidean geometry.

Requirements  are a very good university degree in mathematics  or in computer science and closely related  fields with strong theoretical/methodological focus; curiosity and  strong interest in rigorous, methodical  fundamental research; very good programming skills, preferable in Python; very good command  of written and  spoken English. Prior knowledge in linear algebra, mathematical geometry, stochastics  and optimization is preferable.
Details can also be found in the official vacancy  text:
https://www.verw.tu-dresden.de/StellAus/stelle.asp?id=9603  (German version)

https://www.verw.tu-dresden.de/StellAus/stelle.asp?id=9603&lang=en  (English version)

For further inquiries concerning the position please contact Martin Keller-Ressel ([email protected]).