Umeå University, Mathematics and Mathematical Statistics

scholarship ID:

2216-POSTDOC7 [#28425]

scholarship Title:

Postdoctoral scholarship (2 years) within geometric deep learning

scholarship Type:

Postdoctoral

scholarship Location:

Umea, Vasterbottens Lan 901 03, Sweden

Subject Area:

Geometric deep learning

Appl Deadline:

2026/05/31 23:59:59 (posted 2026/05/13, listed until 2026/05/31)

scholarship Description:

The Department of Mathematics and Mathematical Statistics is offering a postdoctoral scholarship within the project “Geometry-Aware Autoencoders for Reliable Anomaly Detection”. The scholarship is full-time for two years, starting on 1 September 2026 or by agreement.

Department-specific information: At the Department of Mathematics and Mathematical Statistics, we conduct research in both pure and applied mathematics. Research topics range from computational mathematics to the mathematical foundations of artificial intelligence. Within this environment, the research group in geometric deep learning is focused on developing the theoretical underpinnings of modern machine learning. We do this by using geometry to understand structured data, symmetries, and training dynamics, and by leveraging tools from, e.g., differential geometry to create novel models and analyse their properties. More information about our research can be found at https://www.umu.se/en/research/groups/geometric-deep-learning/.

Project description: Autoencoders used for anomaly detection are central to modern data-driven discovery but are prone to poor performance when the problem has nontrivial geometric structure. An example of such a problem is the search for new physics beyond the standard model; the quest for a more complete understanding of the Universe. Experimental data is subject to geometric constraints arising from both physical laws and collider design, resulting in a detection problem that is as challenging as it is scientifically important.

The central goal of this project is to use neural ordinary differential equations (NODEs) on stratified spaces to create flow-based autoencoders that simultaneously accommodate the topology imposed by relativistic particle physics and the geometric constraints from particle detector systems. We will use tools from differential geometry to develop novel geometric deep learning models and explore their properties by training them on (simulated) data from real particle detectors (e.g., the LHC).

The project sits at the intersection of mathematics, physics and computer science, an area that is currently very active due to remarkable recent advances in scientific machine learning. The postdoctoral fellow will have the opportunity to participate in research in this exciting field in close collaboration with the geometric deep learning group at Umeå University. The appointed candidate will be able to hone their skills through access to experts in both differential geometry and particle physics and to develop their independence in a deep learning research environment with excellent opportunities for cross-disciplinary collaborations.

This postdoctoral scholarship is financed and administered by the Kempe Foundations (JCSMK261-0037). The stipend is tax-free and will be 750 000 SEK for two years, meaning 375 000 SEK per year.

Life in Umeå: Umeå is a young, creative, and steadily growing city of about 135,000 people, where students make up a big part of everyday life. That mix gives the city an easy-going yet lively feel, with plenty of cafés, pubs, small venues, and cultural events, without the stress or pace of a big city.

Day to day, though, Umeå is simply a comfortable place to live, safe, compact, and easy to get around, especially by bike. As the largest city in northern Sweden, it offers what you need while staying friendly, calm, and close to home. What people often appreciate most is how close you stay to nature here.

Read more and apply: https://umustipendie.varbi.com/en/what:job/jobID:935515/

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Contact: Fredrik Ohlsson

Email: email address

Postal Mail:

: Department of Mathematics and Mathematical Statistics
Linneaus väg 49
901 87 Umeå
SWEDEN

Web Page: https://www.umu.se/en/department-of-mathematics-and-mathematical-statistics/