The Mathematics of Machine Learning Group, led by Philipp Petersen at the University of Vienna, is excited to announce an opening for a three-year postdoctoral position in the framework of the FWF project:
”Structured Singularities in Deep Learning”.
In deep learning, structured singularities arise, for example, as decision boundaries in a classification problem. Problems where structured singularities are present form some of the few problem cases where deep neural networks are provably superior to all classical machine learning techniques. It can be shown that certain parameters, such as the regularity or size of the decision boundary, as well as related problems, such as the margin and the interplay of noise with the boundary, have a quantifiable effect on the learnability of a problem, as well as on how well-learned classifiers generalize. In this project, these singularities and their effect on the learnability of functions will be studied in a principled way.
The position has a work-load of 40hrs/week and has no teaching duties. The salary is in accordance with collective labor agreements; see https://personalwesen.univie.ac.at/en/jobs-recruiting/job-center/salary-scheme/. The prefered starting date is in Autumn/Winter 2023.
We are searching for a mathematician with a recent PhD. The candidate is expected to conduct independent and collaborative research in the project as well as mentor and collaborate the junior team members. This includes collaboration with the project partners at the University of Tokyo. Moreover, a strong background in machine learning, probability theory, functional analysis, or applied harmonic analysis is necessary. A background in geometric measure theory would be beneficial but not required.
Interested applicants are invited to submit their application, preferably in a single PDF file. The application should include a cover letter, CV, and contact details for two references. Applications should be sent to philipp.petersen@univie.ac.at.
While the position will remain open until filled, to ensure full consideration, we recommend submitting your application before July 15th, 2023.
The University pursues a non-discriminatory employment policy and values equal opportunities as well as diversity. The University puts special emphasis on increasing the number of women in academic positions. Given equal qualifications, preference will be given to female applicants. |
finished (2023/05/23, finished 2023/12/06, listed until 2023/07/22)