Role overview
CLINDA (Centre for Clinical Data Science), Aalborg University Hospital, is looking for a talented and motivated data scientist for a project done in collaboration with the Centre for General Practice, Aalborg University. The position is part time (50%) and runs from 1 May 2026 until 31 October 2028.
About Centre for Clinical Data Science
CLINDA was established in 2022 in collaboration between Aalborg University Hospital and Aalborg University. CLINDA aims to conduct independent research within development, application, and implementation of data infrastructures for AI-based decision support tools. In addition, our intention is to assist relevant research environments at Aalborg University Hospital/Aalborg University in implementing projects and providing advice to relevant authorities within the area. It is also part of the centre's work to develop pre- and postgraduate teaching at Aalborg University but also to participate in national continuing education activities. Our rapidly growing centre, currently 20 people, has a strong ambition to make use of AI for data-driven personalized medicine based on health data and especially genomic data and FAIR data management a reality.
About the position
The 2024 Danish Healthcare reform has outlined the need for integrating the different healthcare sectors into a more coordinated system, with a key focus of these reforms being to improve prevention of chronic disease and disorders, notably through better use of corresponding health data.
These data are nevertheless collected and stored across sectors, notably at general practitioner clinics, hospitals, and municipal bodies, but they have the potential to contain embedded connections between observations, symptoms, and measurements with patient outcomes for a more holistic understanding of the patient journey.
However, due to technical and legal challenges, limited research has been possible on cross-sectorial Danish health data, despite the clear potential of its contents. Another challenge is that a significant portion of these data is in unstructured text format, which requires extra processing steps notably to extract relevant clinical information using Natural Language Processing (NLP) methods.
We are looking for a data scientist who will explore the use of these datasets to develop predictive models for clinical outcomes in cross-sectoral use cases leveraging NLP approaches, to allow for more personalized care.
The position aims at exploring the following topics:
demonstrate the extent to which unstructured text from cross-sectoral electronic health journals can be extracted using NLP methods to obtain clinically meaningful and useful information
develop clinical outcome predictive models based on electronic health records (EHRs) with the purpose of identifying patients with heightened risk profiles across different healthcare domains
demonstrate how cross-sectorial healthcare datasets can improve the predictive performance of patient outcomes relative to single source datasets.
We offer
We offer a rewarding and challenging job in an interdisciplinary environment. We strive for academic excellence in an environment characterised by collegial respect and academic freedom tempered by responsibility.
Qualification requirements
The potential of each applicant will be emphasized based on an overall assessment of the following qualifications:
- MSc in data science, or a closely related field (engineering, statistics, bioinformatics...)
- Experience with clinical data and research
- Experience in machine learning programming, e.g., R, Stata, Python, or SAS
- Experience with data management and analysis of large data sets
- Motivated by interdisciplinary research
- Excellent writing and communication skills in English with a good scientific vocabulary
TILTRÆDELSE:
*01. maj 2026