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 seeks a postdoctoral researcher in Computer Science with focus on AI trustworthiness modeling in medical domain. The employment of full-time for two years starts in Feb 2026 or by agreement. The deadline for applications is Nov 28, 2025.
Department of Computing science
At our institution, which conducts research at the highest international level and offers several high-quality educational programs in Computer Science, we are now seeking a postdoctoral researcher with a focus on AI trustworthiness modeling on multimodal data and machine learning models.
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:
Is this interesting for you? Welcome with your application before Nov 28, 2025.
Project description and working tasks
This position is funded by the European project COMFORT (www.comfort-ai.eu) and the AI Policy Lab in Umeå University (www.aipolicylab.se). COMFORT (Improve Diagnosis and Treatment of Urologic Cancers with Artificial Intelligence-Driven Decision Support Tool) is developing a cutting-edge decision support system using artificial intelligence (AI) and data-driven approaches to assist medical professionals in delivering improved care for people affected by prostate cancer (PCa) or kidney cancer (KC).
The first phase of this postdoctoral research will focus on modeling AI trustworthiness and explainability in medical data and models, with particular emphasis on fairness and privacy. The second phase will explore integrating AI governance and policy with the outcomes achieved in the first phase.
The successful candidate will be part of the Responsible Artificial Intelligence group and the Deep Data Mining group at the Department of Computing Science, collaborating with researchers in, e.g., data science, machine learning, and responsible AI. More info about the research groups: https://www.umu.se/en/department-of-computing-science/research/research-groups/.
Qualifications
To be appointed under the postdoctoral agreement, the postdoctoral fellow is required to have completed a doctoral degree or a foreign degree deemed equivalent to a doctoral degree. This qualification requirements 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 doctoral degree, according to what is stipulated in the paragraph above, no later than three years prior. If there are special reasons, candidates who completed their doctoral degree prior to 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.
The successful candidate should hold a doctorate or a foreign qualification equivalent to a doctorate in computer science, mathematics, or engineering physics.
Requirements:
Comprehensive knowledge and practical skills in the field of data science, especially multimodal data analysis.
Experience on image processing via machine learning.
Programming skills (e.g., Python) are required.
Ability to communicate effectively in both spoken and written English.
Merits:
Research experience on natural language processing, causal inference.
Research experience on medical domain.
Knowledge of AI trustworthiness-related topics (e.g., fairness or explainable).
Knowledge on AI governance related.
Application
A full application should include:
cover letter in which you provide a brief description of your research interests and a statement describing why you are interested in the position,
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 five 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 and 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 Nov 28, 2025. Further details are provided by associate professor Lili Jiang (lili.jiang@umu.se) and professor Virginia Dignum (virginia@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.
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