Two PhD stipends for the AI:GENE-XPLAIN Lab

Job Description

The AI:GENE-XPLAIN Lab is part of the AI:X initiative with two PhD stipends and is a collaboration between the Department of Culture and Communication, the Faculty of Social Sciences and Humanities and the Center for Clinical Data Science (CLINDA), Department of Clinical Medicine, the Faculty of Medicine.

AI:GENE-XPLAIN develops AI tools that predict genetic cancer risk and help explain these risks to people in a clear and safe way. One part of the project builds AI models that can predict the risk of several cancers at once and explain how genes influence that risk. Another part studies how people understand and react to these predictions, so the information supports good decisions without causing unnecessary worry.

The two stipends are open for appointment from 15 August 2026 or soon hereafter. The duration of the position is three years.

Stipend 1: AI-Based Genetic Risk Prediction (AI-focused)

This position focuses on developing cutting-edge AI methods for genetic risk prediction across multiple cancer types, with a strong focus on model performance and explainability. The project will involve designing a transformer-based foundation model for genetic data, with an integrated prediction layer for colorectal cancer screening. Subsequently, the framework will be extended to multi-task learning for multi-cancer risk prediction. To develop these models, you will have access to unique biobank data containing genetic information linked to Danish registry data for approximately 250,000 individuals. You will also work on incorporating explainability features identified by the AI-integrated PhD to support risk-based cancer screening and ensure clinical relevance and usability.

Genetic risk predictions from the model will be used by the AI-integrated PhD to examine how individuals’ behavior and psychological safety are affected. The ideal candidate has completed, or is about to complete, a master’s degree in computer science, mathematics, statistics, IT, engineering, biotechnology, bioinformatics, economics, or a related field. Experience with programming in Linux environments, Python and/or R, and ability to manage and structure large datasets is essential. Interest/skills in application of AI methods to clinical data is an advantage.

Stipend 2: Genetic Risk Communication and Psychological Safety (AI-integrated)

This position focuses on understanding how individuals and clinicians perceive, interpret, and respond to AI-generated genetic risk predictions, and on developing communication strategies that support informed decision-making and psychological safety at scale. You will conduct studies involving questionnaires and interviews with a representative sample of the adult population and clinicians, interviews with individuals from colorectal cancer screening programmes with high-risk results, and an intervention study examining the effects of receiving genetic risk information on behaviour and quality of life.

Your insights will directly shape the explainability features developed in the AI-focused PhD project. The ideal candidate holds a master's degree in psychology or is in the process of completing one. Experience with qualitative methods and an interest in health behaviour, risk communication, or clinical psychology is essential. Some clinical experience is an advantage.

Your competencies:

For both stipends, we value a genuine interest in the societal implications of AI in healthcare, the ability to work independently and as part of a team, and strong written and oral communication skills in English.

Given the interdisciplinary nature of the project, we are looking for candidates who are intellectually curious, collaborative, and motivated to work across disciplinary boundaries. You are comfortable engaging with both technical and humanistic perspectives and communicate effectively with researchers and clinical partners from diverse backgrounds.

How to apply:

Your application must include the following:

• Application, stating reasons for applying and qualifications in relation to the position
• Curriculum Vitae (CV)
• Diplomas for the Bachelor’s and Master’s degrees (the Master’s degree may be completed or expected to be completed shortly), including grades.
• If you are applying for stipend 2: Project description containing the research project title, an outline of the course of study and a description of the overall problem areas (approx. 8 pages, 1 page = 2400 typing units)
• If you are applying for stipend 2: Applicants WHO are planning to complete a doctoral thesis in English and who do not have English as a first language or WHO have not completed an English language-based Master's programme (or an equivalent educational achievement in English) shall provide documentation that they have passed one of the following official tests with the respective minimum score: IELTS (band score): 7, TOEFL (paper-based): 600, TOEFL (internet-based): 100. The language test must be no more than five years old at the time of the application.
• If you are applying for stipend 2: Applicants must have achieved the grade 10 or above in the Danish grading system (or the equivalent in a different grading system) for their Master’s Thesis/final exam. The PhD candidate may be exempted from the grade requirement, if he/she is able to provide other forms of documentation of his/her qualifications.
• Other relevant documents

The application must be submitted via Aalborg University’s recruitment system, which can be accessed under the job advertisement on Aalborg University's website.