Vacant job

Umeå University is one of Sweden's largest institutions of higher education with over 37,000 students and approximately 4,700 employees. The university offers a diversity of high-quality programs and world-leading research in several scientific fields, and it was here that the groundbreaking discovery of the CRISPR-Cas9 gene-editing tool was awarded the Nobel Prize in Chemistry. At Umeå University, everything is close. Our cohesive campuses make it easy to meet, collaborate, and exchange knowledge, fostering a dynamic and open culture.

The societal transformation and the large green investments we see in northern Sweden create enormous opportunities and complex challenges. For Umeå University, this means conducting research about – and in the midst of – a transforming society. It is also about delivering education for regions that need to expand quickly and sustainably. This is simply where the future is created.

Are you interested in learning more? Read more here (https://www.umu.se/jobba-hos-oss/om-universitetet-som-arbetsplats/).

We are now looking for a postdoctoral researcher to work on privacy-preserving methods for data-driven models at our institution, which conducts research at the highest international level and offers several high-quality educational programs.

The position is full-time for two years, starting April 1, 2026, or by agreement.

For more information about the Department of Computer Science: Read more here (https://www.umu.se/institutionen-for-datavetenskap/).

Project Description and Responsibilities

The project will develop privacy-aware models for machine learning (ML). We are interested in data-driven models for complex data, including temporal data. We are interested in both data-driven models and models built from synthetic data. In the area of privacy, we work with various types of privacy metrics and models (differential and integral privacy, k-anonymity) as well as different scenarios (centralized and decentralized data; local and global privacy). For decentralized data, we consider federated learning. We are interested in large-scale privacy-preserving machine learning.

The research group Privacy-aware transparency decisions, led by Professor Vicenç Torra, researches data privacy for data intended for machine learning and statistical purposes. It is well-known that data can be very sensitive and that naive anonymization is not sufficient to avoid disclosure. Models and aggregates can also lead to disclosure as they may contain traces of the data used in the computation. We want to understand the fundamental principles that allow us to build privacy-aware AI systems and develop algorithms for this purpose. The group collaborates with several national and international research groups, is an editor for one of the largest journals on data privacy (Transactions on Data Privacy), and has active contacts with the private and public sectors. For more information see: Read more here (https://www.umu.se/en/research/groups/nausica-privacy-aware-transparent-decisions-group-/).

The postdoctoral position is funded by WASP. Read more: Read more here (https://wasp-sweden.org/).

Qualifications

To be employed under the fixed-term employment agreement as a postdoctoral researcher, a completed doctoral degree or a foreign degree deemed equivalent to a doctoral degree is required. This eligibility requirement must be met no later than when the employment decision is made.

To be employed under the postdoctoral agreement, preference will primarily be given to those who have obtained their degree as mentioned in the previous paragraph within the last three years. If there are special reasons, those who obtained their doctoral degree earlier may also be considered. Special reasons refer to leave due to illness, parental leave, union duties, service in the total defense, or other similar circumstances, as well as clinical service or relevant service/assignment in the subject area.

A qualified applicant should have a doctoral degree or a foreign degree deemed equivalent in computer science or another subject relevant to the project.

Documented knowledge and proven research experience in the design of algorithms and methods for data protection and machine learning is required. Publications at leading conferences in machine learning, security, and privacy (NeurIPS, ICML, S&P, PETs, ESORICS, or similar conferences) are highly meritorious.

A successful candidate is expected to have a scientific and results-oriented approach to their work. Excellent proficiency in the English language, both spoken and written, is a key requirement.

Application

A complete application should include:

• A personal letter describing your research interests and why you are applying for the advertised position. Summarize your qualifications, research interests, motivation for applying, and describe the connection between your previous research and the position (max 2 pages),
• Curriculum vitae - CV with a publication list,
• Certified copy of the doctoral degree certificate or documentation confirming when the doctoral degree is expected to be obtained,
• Certified copies of other degree certificates, academic course certificates, and/or transcripts,
• A copy of the doctoral thesis and a maximum of 5 relevant articles,
• Other documents that the applicant wishes to submit.
• Contact information for two referees.

The application should be written in English or Swedish. Applications are made through our electronic recruitment system. Documents sent electronically should be in Word or PDF format. Log in to the system and apply via the button at the end of this page. The application deadline is February 3, 2026. For further information, please contact Vicenç Torra at [email protected] (mailto:[email protected]).

Umeå University aims to provide an equal and equitable environment where open conversations between people with different backgrounds and perspectives lay the foundation for learning, creativity, and development. We therefore welcome individuals with diverse backgrounds and experiences to apply for this position.

To staffing and recruitment agencies and to you as a seller: We kindly but firmly decline direct contact with staffing and recruitment agencies and sellers of additional job advertisements.