[Jobs] Postdoctoral scholarship in Geometric Deep Learning / Scientific ML, Umeå University — deadline 31 May 2026
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Per Åhag
May 19, 2026, 4:00:30 PM (7 days ago) May 19
to Women in Machine Learning
Dear colleagues,
Umeå University’s Department of Mathematics and Mathematical Statistics invites applications for a two-year postdoctoral scholarship in geometric deep learning within the project “Geometry-Aware Autoencoders for Reliable Anomaly Detection.”
The project develops geometry-aware autoencoder methods for anomaly detection, using neural ODEs on stratified spaces and flow-based models that incorporate geometric and topological constraints. The application domain includes simulated data from real particle detectors, for example the LHC. The project sits at the intersection of mathematics, physics, computer science, geometric deep learning, and scientific machine learning.
Suitable backgrounds include mathematics, physics, computer science, scientific machine learning, differential geometry, differential equations, geometric deep learning, or machine learning for particle physics. Good programming skills and documented experience implementing machine learning models and methods are required.
Location: Umeå University, Sweden
Start: 1 September 2026 or by agreement
Duration: 2 years, full time
Stipend: 750,000 SEK over two years, tax-free
Deadline: 31 May 2026
Contact: Associate Professor Fredrik Ohlsson, fredrik...@umu.se
Application and full details:
https://www.umu.se/en/work-with-us/postdoctoral-scholarships/postdoctoral-scholarship-2-years-within-geometric-deep-learning_935515/
Umeå University welcomes applicants with different backgrounds and experiences and especially encourages female applicants.
Best regards, Per
Umeå University’s Department of Mathematics and Mathematical Statistics invites applications for a two-year postdoctoral scholarship in geometric deep learning within the project “Geometry-Aware Autoencoders for Reliable Anomaly Detection.”
The project develops geometry-aware autoencoder methods for anomaly detection, using neural ODEs on stratified spaces and flow-based models that incorporate geometric and topological constraints. The application domain includes simulated data from real particle detectors, for example the LHC. The project sits at the intersection of mathematics, physics, computer science, geometric deep learning, and scientific machine learning.
Suitable backgrounds include mathematics, physics, computer science, scientific machine learning, differential geometry, differential equations, geometric deep learning, or machine learning for particle physics. Good programming skills and documented experience implementing machine learning models and methods are required.
Location: Umeå University, Sweden
Start: 1 September 2026 or by agreement
Duration: 2 years, full time
Stipend: 750,000 SEK over two years, tax-free
Deadline: 31 May 2026
Contact: Associate Professor Fredrik Ohlsson, fredrik...@umu.se
Application and full details:
https://www.umu.se/en/work-with-us/postdoctoral-scholarships/postdoctoral-scholarship-2-years-within-geometric-deep-learning_935515/
Umeå University welcomes applicants with different backgrounds and experiences and especially encourages female applicants.
Best regards, Per
Per Åhag, Umeå University
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