Open Postdoc Position in Machine Learning at Aalborg University

  • 11 June 2024

A new postdoctoral position in machine learning within the ARISTOTELES project is now available at the Center for Clinical Data Science, Department of Clinical Medicine, Aalborg University. This two-year position will commence around 1 September 2024. 

The position 

The Center for Clinical Data Science (CLINDA) is a part of both the Department of Clinical Medicine at Aalborg University and the Research, Education, and Innovation department at Aalborg University Hospital. CLINDA focuses on the application and methodological development of bioinformatics, biostatistics, machine learning, and data management within clinical research.  

The successful candidate will join the ARISTOTELES project team, contributing to leverage artificial intelligence for personalized prediction and early detection of comorbidity and multimorbidity patterns in atrial fibrillation patients.  

Key responsibilities will include structuring health data for machine learning algorithms (feature engineering), developing machine learning-based algorithms for predicting complications related to atrial fibrillation, and implementing predictive models in clinical settings. The candidate will work with key stakeholders across Europe and collaborate closely with researchers at the Danish Center for Health Services Research and the Center for Clinical Data Science, as well as the Department of Computer Science at Aalborg University. 

  • Area: Center for Clinical Data Science
  • Contract Duration: 2 years
  • Expected Start Date: 1 September 2024
  • Application Deadline: 28 June 2024 

Necessary qualifications 

Applicants should hold a PhD in computer science, statistics, physics, mathematics, engineering, or a related data science field. Extensive experience with machine learning, strong programming skills (ideally in Python), and experience with healthcare data are required. Additional desirable qualifications include web development experience, prior knowledge in cardiology, experience with Danish register data, and familiarity with Electronic Patient Journal systems. 

Valued personal competencies include independence, creativity, a proactive attitude, proficiency in English, flexibility, and a result-oriented mindset. 

This position offers a unique opportunity to work in a multi-disciplinary, collaborative environment at the intersection of computational healthcare and machine learning. For further information please click here.