PhD student position (f/m/d) on optimization methods for deep learning (Ref. 22/34) at WIAS, Berlin, Germany
WIAS invites in the Research Group
“Nonsmooth Variational Problems and Operator Equations”
(Head: Prof. Dr. M. Hintermüller) applications for a
PhD student position (f/m/d)
on optimization methods for deep learning
to be filled at the earliest possible date. The position is associated to the MATH+ Cluster of Excellence project EF1-15 “Robust Multilevel Training of Artificial Neural Networks”. The project aims to develop novel methods for training nonsmooth artificial neural networks with emphasis on their theoretical analysis, algorithmic implementation and related applications (e.g. deep learning-based numerical solution of PDEs and their optimal control).
We are looking for: a motivated and enthusiastic candidate with an above-average master’s degree in mathematics and a solid background in mathematical optimization, numerical analysis, scientific computing, functional analysis and partial differential equations. Strong programming skills are highly desired.
Technical queries should be directed to Prof. Dr. Michael Hintermüller (Michael.Hintermueller@wias-berlin.de).
The position is limited to three years. The reduced work schedule is 29,25 hours per week, and the salary is according to the German TVoeD Bund scale.
The Institute aims to increase the proportion of women in this field, so applications from women are particularly welcome. Among equally qualified applicants, disabled candidates will be given preference.
Please upload your complete application documents (motivation letter, detailed CV, certificates, list of MSc courses and grades, copy of the master thesis, reference letters, etc.) via our applicant portal using the button “Apply online”.
The advertisement is open with immediate effect and will remain open until the position will be filled.
We are looking forward to your application!
See here for more information: https://short.sg/j/22798226