Postdoc in Artificial Intelligence and Machine Learning for Clinical Decision Support

Join a research environment where Artificial Intelligence and Machine Learning moves beyond theory into clinical impacts. At the Faculty of Engineering and Science, this postdoctoral position offers the opportunity to develop intelligent technologies, collaborate across scientific, engineering and clinical disciplines, and contribute to innovations shaping the future of clinical and healthcare systems. This full-time position is available for a period of two years from 1st of October 2026, with the possibility of extension.

Your work tasks

We are seeking a highly motivated postdoctoral researcher in artificial intelligence and machine learning for clinical decision-support systems and disease prediction modeling to join our research group.

The successful candidate will develop and apply advanced AI methodologies for clinical research and healthcare applications to support decision-making in cancer care. The work will include, but will not be limited to, multimodal data integration, image processing and analysis, longitudinal and time-series data modeling, predictive analytics, and the development of generative AI solutions for clinical decision support. The candidate will contribute to the design and implementation of AI-driven solutions tailored to complex biomedical and healthcare research challenges.

The successful candidate will contribute to, among others, an EU-funded project focused on AI-driven modeling of lung cancer progression. This role offers a broad and unique perspective at the intersection of clinical research and artificial intelligence, as well as the opportunity to develop solutions with real-world clinical impact. The candidate will collaborate closely with a multidisciplinary and international team, including clinical researchers (radiologists and oncologists), AI/ML researchers, and biostatisticians.

Your competencies

You should demonstrate a strong computational profile and hands-on experience working with complex datasets, alongside high proficiency in programming languages such as Python, R, or similar.

The successful candidate should have a strong background in data science, artificial intelligence, and advanced analytical methods. Experience in AI/ML model development for complex and heterogeneous datasets will be considered an advantage. Experience working with clinical data or clinical projects, including integration of heterogeneous clinical data and validation of AI/ML solutions in real-world clinical settings, will also be considered an advantage.

We value candidates who are proactive, collaborative, and able to work effectively across multidisciplinary environments. Strong written and spoken English communication skills are essential.

Qualification requirements

Appointment as postdoc requires academic qualifications at PhD level. Applicants must hold a PhD in mathematics, computer science, bioinformatics, engineering, or a related data science discipline.

Applicants must have documented research experience within artificial intelligence, machine learning, computational methods, or data-driven modelling. Experience conducting independent research and disseminating results through peer-reviewed publications is required.

Applicants are expected to demonstrate the ability to contribute to interdisciplinary research environments and collaborate across academic, clinical, and external stakeholder settings.

Who we are

The AI4OR group operates at the intersection of artificial intelligence and machine learning, operations research and optimization, developing advanced computational and decision-support methodologies for complex real-world challenges. The group conducts research spanning both methodological innovation and applied problem solving, including novel AI algorithms, hybrid AI-OR techniques, generative and predictive modelling, data-driven optimization, and intelligent decision-support systems. The group maintains extensive collaborations with industry partners and hospitals, both in Denmark and internationally, ensuring strong translational impact and real-world application of developed methodologies.

Research activities cover applications across healthcare and clinical decision support, as well as industrial domains such as logistics, routing, maintenance planning, and autonomous and mobile systems. Within the clinical domain, the group develops and applies advanced AI methodologies for disease modelling, prediction, and clinical decision support, with a strong focus on translating data-driven methods into real-world healthcare applications.

The Department of Materials and Production (MP) is a wide-ranging research and educational environment at Aalborg University. The Department's mission is to meet the future's demands for new materials and production systems by directing the whole value chain from basic material understanding to materials' applications in mechanical construction, industrial production, and management.

How to apply

Your application must include the following:

• Application, stating reasons for applying, qualifications in relation to the position, and intentions and visions for the position
• Curriculum Vitae (CV)
• Diplomas (master's degree diploma and PhD diploma)
• List of publications, with an indication of the attached publications that you wish to be taken into account in the assessment. You may attach a maximum of five publications.
• Documentation of teaching qualifications if relevant.
• Dissemination qualifications, including participation on committees or boards, participation in organisations etc.
• Additional qualifications in relation to the position
• References/recommendations

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

Salary and terms of employment

The employment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities and the Ministerial Order on Job Structure for Academic Staff at Universities. Salary and terms of employment are in accordance with the collective agreement between the Danish Confederation of Professional Associations and the state. There is a mutual probationary period of 3 months for the position.

Further information

Read more about our recruitment process here.