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Position: Lead AI postdoctoral research fellow position within Reeb graph learning
Institution: University of Bergen
Location: Bergen, Hordaland, Norway
Duties: Manifold learning is a crucial concept in the fields of machine learning and pattern recognition, because it enables the discovery and representation of underlying structures and patterns in high-dimensional data. In real-world scenarios, datasets often exhibit intricate manifold structures and the pursuit of capturing these complex geometries within the data has proven to be a challenging task for many traditional manifold learning algorithms. While it may not always be possible to fully learn the underlying manifold, it is often possible to learn some characteristics of the manifolds. One such characteristic is the Reeb graph, a topological construct that reflects the change of level sets of a real-valued filter function on a manifold
Requirements: Applicants must hold a Norwegian PhD or an equivalent degree machine learning or a related area; Applicants should have a genuine interest in AI, and the research proposal must be related to artificial intelligence
   
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