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., 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., * 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

Do you have experience in Research?, Do you have a Master's degree?, 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.

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. The department has several strong, international, and innovative research groups that comprise everything from basic science to strategic and applied research. The activities encompass research and education within materials, mechanics, physics, production, and industrial management and innovation. Several innovative and unconventional collaborations have been and are being developed through interdisciplinary cooperation, benefiting the industry and additional collaborators. As an employee at the department, you will become part of an international research environment focusing on innovation, knowledge sharing/building, and interdisciplinary collaborations. The Department's activities are supported by world-class laboratories and an important part of the research being done at the department. Specifically in relation to this position we have facilities for synthesis and characterization of materials covering the range from the atomic scale in the cleanroom and materials labs to fabrication of components and devices., The appointment process at Aalborg University involves a shortlisting process. You can read more about the shortlisting and appointment process here. The hiring process at Aalborg University may include a risk assessment as a tool to identify potential risks associated with new hires, ensuring the safety, compliance, and integrity of the workplace. Salary and terms of employment The employment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities (the Appointment Order) and the Ministerial Order on Job Structure for Academic Staff at Universities (in Danish) and protocol on certain terms of employment of academic staff at universities (in Danish). Salary and terms of employment are in accordance with the collective agreement between the Danish Confederation of Professional Associations and the state (AC collective agreement) (only in Danish) and protocol on certain terms of employment of academic staff at universities (only in Danish). There is a mutual probationary period of 3 months for the position. Aalborg University - Knowledge for the world Aalborg University is an international workplace with more than 3,700 employees. We offer real-world-oriented education and create world-class research results through collaboration between researchers, students, and public and private companies. This is how we achieve insights, new solutions to societal problems, and knowledge that changes the world. Our main campus is in Aalborg, but we also have campuses in Esbjerg and Copenhagen.