Postdoctoral Position(s)

Applications are invited for the position of Postdoctoral Researcher at the Institute of Mathematics of the Ecole Polytechnique Fédérale
de Lausanne (EPFL)
.

The position will be in the Chair of Mathematical Statistics, mentored by Prof. Victor Panaretos.

The envisioned research projects fall within the broad theme of statistical analysis for/with random functions, measures, and operators. The overarching goal is not only to extend classical statistical ideas into infinite-dimensional settings, but also to exploit phenomena unique to infinite dimensions, and even translate infinite-dimensional insights back into finite-dimensional methods.

Possible directions include:

  • Statistical Optimal Transport and Probability Flows, especially in the Bures–Wasserstein space of covariance operators.
  • Functional Data Analysis and Stochastic Dynamics, including nonparametric methods for SDE in function spaces.
  • Graphical and Likelihood Methods for random vectors with functional entries, including Gaussian correlation operator theory.
  • Nonparametric inference and functional Inverse problems with  kernel methods and embeddings.

The position will be available as of September 1st, 2026.

Candidates should hold a PhD in Statistics, Mathematics, or a related field by the starting date. Knowledge of French is not a requirement, but would be helpful.

To apply, please submit the following material:

  • CV (including the names and addresses of three referees)
  • List of publications.
  • Research statement.
  • One reprint/preprint.

Applications submitted by November 15th are guaranteed consideration. Short-listed candidates may be invited for an interview.

All files should be sent as attachments in PDF format to the Chair’s secretary:

Maroussia Schaffner Portillo: [email protected]

including a brief cover letter in the main body of the email and subject: “Application for Postdoc / Last name”.

Candidates should ask their three referees to send their letters directly to the same email address.