Umeå University is one of Sweden’s largest higher education institutions with over 37,000 students and about 4,700 employees. The University offers a diversity of high-quality education and world-leading research in several fields. Notably, the groundbreaking discovery of the CRISPR-Cas9 gene-editing tool, which was awarded the Nobel Prize in Chemistry, was made here. At Umeå University, everything is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture.
The ongoing societal transformation and large green investments in northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here.
The Department of Computing Science at Umeå University is looking for a doctoral student in machine learning. The position is for four years of full-time doctoral studies at the Department of Computing Science, where you will be able to work in a dynamic environment with about 170 employees from more than 20 countries.
The Department of Computing Science has been growing rapidly in recent years, with a focus on creating an inclusive and bottom-up driven research environment. Our workplace consists of a diverse set of people from different nationalities, backgrounds and fields. As a PhD student working with us, you receive the benefits of support in career development, networking, administrative and technical support functions, along with good employment conditions. More information about the department is available at: Department of Computing Science.
Project description Machine learning is a key technique in many research and development areas, and machine learning accounts for much of the recent success in artificial intelligence. 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.
The doctoral student position is offered within the machine learning project “The Challenges for Machine Learning in Medical Imaging: Lack of Data and Trust” that is financed by the Swedish Research Council. The project is led by Tommy Löfstedt, docent and associate professor at the Department of Computing Science, Umeå University.
Requirements 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.
Important personal qualities include the ability to work on your own as well as together with others. You are also creative, and have a will to actively develop yourself to become a competent researcher.
About the position The position provides you with the opportunity to pursue PhD studies in Computing Science for four years, with the goal of achieving the degree of Doctor in Computing Science. While the position is mainly devoted to PhD studies (at least 80% of the time), it may include up to 20% department service (usually teaching). If so, the total time for the position is extended accordingly, resulting in a maximum of five years.
Wage placement takes place according to the established salary ladder for doctoral student employment. According to the Higher Education Ordinance (Chapter 12, Section 2), the decision on employment cannot be appealed.
The expected starting date is May 4, 2026, or as otherwise agreed upon.
Application Applications must be submitted electronically using the e-recruitment system of Umeå University.
A complete application should contain the following documents:
A cover letter including a description of your research interests and your reasons to apply for the position. The cover letter should also contain your contact information, and documentation and description of how you fulfill the specified requirements.
Curriculum Vitae (CV).
Certified copies of degree certificates, including documentation of completed academic courses and obtained grades.
Copies of completed BSc and/or MSc theses and other relevant publications, if any.
Contact information to 2-3 references.
Documentation and description of other relevant experiences or competences.
The application must be written in English or Swedish. Attached documents in other languages should be translated. Attached documents must be in pdf format.
Applications must be submitted electronically using the e-recruitment system of Umeå University, and be received no later than January 25, 2026.
The Department of Computing Science values gender diversity, and therefore particularly encourages women and those outside the gender binary to apply for the position.
For additional information, please contact associate professor, docent Tommy Löfstedt (tommy.lofstedt@umu.se).
Umeå University wants to offer an equal environment where open dialogue between people with different backgrounds and perspectives lay the foundation for learning, creativity and development. We welcome people with different backgrounds and experiences to apply for the current employment.
We kindly decline offers of recruitment and advertising help.
