Topological Data Analysis and Data Science

We are looking for a researcher in Mathematics or Computer Science who will work at the interface between the mathematics of data analysis (in particular, Topological Data Analysis) and Data Science. Recent advances in computational topology have made it possible to compute topological invariants from data with the aim to reconstruct computationally the topological features of some low-dimensional set, only observed via a high-dimensional noisy point cloud. This relates to well-known approaches in Data Science, including clustering, feature extraction, manifold learning, nonlinear dimension reduction, information geometry, and distinguishing (topological) signal from (topological) noise. The position will be embedded in one of the existing Mathematics or Computer Science research units of the Bernoulli Institute, with strong collaborations with materials science and artificial intelligence.

For more information about the position click here and to apply click here.