Fully Funded PhD Position to Develop Novel Bayesian Machine Learning Methods and Algorithms

[Tommy L]

Dear all,

A fully funded PhD student position in machine learning is available
at the Department of Computing Science, Umeå University, Sweden.

Link to the full offer with all details:
https://www.umu.se/en/work-with-us/open-positions/phd-student-in-computing-science-with-a-focus-on-machine-learning_885344/
Deadline for the application: January 25, 2026.

A great opportunity to work in machine learning, fully funded by the
Swedish Research Council.


Project description

Large-scale machine learning open up for incredible opportunities in
many different applications and has gone through a very rapid
development in the last few years. Large-scale machine learning models
are however notoriously over-confident. With insufficient amounts of
data to train them on together with unknown but presumably large
prediction uncertainties, their broad application is hindered. This is
especially a problem in application areas that require robust and
trustworthy solutions, such as in medical applications.

Federated Bayesian learning offers a solution to those problems by
allowing multiple participants to train machine learning models
collaboratively, without sharing any data. Bayesian models also
provide uncertainty estimates in the model and its predictions,
allowing the confidence in automated decisions to be evaluated.

The goal of this project is therefore to develop learning algorithms
and methods for calibrated Bayesian federated learning for trustworthy
collaborative Bayesian learning on data from multiple participants.
The project will develop new methods, theory, and algorithms for
Bayesian machine learning with applications in e.g., medical image
analysis.


Eligibility

The general admission requirements for doctoral studies are a
second-cycle level degree, or completed course requirements of at
least 240 ECTS credits, of which at least 60 ECTS credits are at
second-cycle level, or have an equivalent education from abroad, or
equivalent qualifications.

To be admitted to doctoral studies in Computing Science, the applicant
must have completed courses totaling at least 90 higher education
credits in Computing Science or in subjects directly relevant to the
specific specialization.

A requirement for this doctoral position is that the applicant is
proficient in the project related areas, and in particular regarding:

- Machine Learning,
- Numerical Methods,
- Probability Theory, and
- Bayesian Methods and MCMC Algorithms.

Proficient programming skills is a requirement. A very good command of
the English language, both written and spoken, is a key requirement.

Experience in Federated Learning, Computer Vision, Image Analysis,
Mathematics, and Mathematical Statistics is a merit.


Apply through the link above!

Looking forward to reading your application!

Kind regards,
Tommy Löfstedt
Associate Professor
Department of Computing Science
Umeå University
Umeå, Sweden