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.
To our institution, which conducts research at the highest international level and offers several high-quality educational programs, we are now seeking a postdoctoral researcher to work on privacy for data-driven models and high-dimensional data. The position is full-time for two years, starting on 8th January 2026, or as agreed upon.
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 postdoctoral researcher 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: https://www.umu.se/en/department-of-computing-science/
Project description and working tasks
The project will develop privacy-aware machine learning (ML) models. We focus on data-driven models for complex and temporal data, including those built from synthetic sources. Within privacy, we are interested in different types of privacy measures and models (differential and integral privacy, k-anonymity), different scenarios (centralized and decentralized data; local and global privacy). For decentralized data, we consider federated learning. We are interested in privacy-preserving machine learning at a scale.
Research group
The Privacy-aware transparency decisions research group (led by Prof. Vicenç Torra) conducts research in data privacy for data to be used for machine and statistical learning. It is well known that data can be highly sensitive, and that naive anonymization is not sufficient to avoid disclosure. Models and aggregates can also lead to disclosure as they can contain traces of the data used in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose.
The group collaborates with several national and international research groups on these topics, and has active links with the private and public sectors. For more information see:
Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish society and industry. Read more: https://wasp-sweden.org/
Qualifications
To be appointed under the agreement on fixed-term employment as a postdoctoral fellow, the candidate is required to have completed a doctoral degree or a foreign degree deemed equivalent to a doctoral degree. This qualification requirement must be fulfilled no later than at the time of the appointment decision.
To be appointed under the postdoctoral agreement, priority should be given to candidates who completed their degree, in accordance with what is stipulated in the paragraph above, no later than three years ago. If there are special reasons, candidates who completed their doctoral degree earlier than that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organisations, military service or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant to the subject area.
A qualified applicant is required to have a PhD degree or a foreign degree that is deemed equivalent in Computer Science, or another subject of relevance for the project.
Documented knowledge and proven research experience in the area of designing algorithms and methods for data privacy and machine learning is required. It is highly meritorious to have publications in top venues in machine learning, and security and privacy (NeurIPS, ICML, S&P, PETs, ESORICS or similar conferences).
A successful candidate is expected to have a scientific and result-oriented approach to your work. A very good command of the English language, both written and spoken, are key requirements.
Application
A full application should include:
Cover letter describing your research interests and why you are applying for the advertised position. Include a summary of your qualifications, research interests, motivation for applying, and briefly describe the connection between your past research and the position (max 2 pages),
Curriculum vitae (CV) with publication list,
Verified copy of doctoral degree certificate or documentation that clarifies when the degree of doctor is expected to be obtained,
Verified copies of other diplomas, list of completed academic courses and grades,
Copy of doctoral thesis and up to 5 relevant articles,
Other documents that the applicant wishes to claim.
Contact information to two persons willing to act as references.
The application must be written in English or Swedish. The application is made through our electronic recruitment system. Documents sent electronically must be in Word or PDF format. Log in to the system and apply via the button at the end of this page. The closing date is 25 nov, 2026. Further details are provided by Vicenç Torra, vtorra@cs.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.
