Postdoctoral Researcher in Machine Learning & Predictive Modelling

at  KUCENTER FOR SUNDHED OG SAMFUND

We are looking for a highly motivated and dynamic postdoctoral researcher for a 3-year position, who is a specialist in predictive modelling to commence 1st December 2024. We are seeking a highly motivated candidate with experience in statistical machine learning to work on methods that combine health records and epidemiological data to develop robust applicable risk prediction models. We are looking for a candidate who has experience in, but not restricted to: implementing machine learning approaches (penalised regression, tree-based algorithms, Super Learner, deep learning models) in real-world scenarios, and analysing large data of electronic health records and nationwide registries.
Information on the group can be found at: mlgh.net

YOUR JOB

We are looking for a specialist in risk prediction modelling. The ideal candidate for this job would have had extensive experience developing and validating classic statistical and machine learning models in real world scenarios, preferably in a clinical framework. Knowledge of epidemiology, study designs and causal inference would be considered a significant advantage. Your day-to-day tasks would be leading applications of statistical and machine learning models to a range of problems in the group including public health, biology, and economics. You will be in charge of developing models in tandem with other researchers in the group, with a focus in applicability. The ideal candidate would already have extensive experience implementing various learners using R and/or Python.

PROFILE

We are looking for a highly motivated and enthusiastic scientist with the following competencies and experience:

Essential experience and skills:

• You have a PhD in epidemiology, data science, bioinformatics, statistics
• You are highly experienced in applying, developing and implementing a range of machine learning models
• You have an active interest in machine learning and statistics
• Proficient communication skills and ability to work in teams
• Excellent English skills written and spoken

Desirable experience and skills:

• Experience/knowledge of R and Python
• Experience/knowledge in machine learning frameworks, e.g. tidymodels, mlr3, scikit-learn
• Experience/knowledge in validation of (clinical) risk prediction models

• Experience in epidemiological analyses of registry data and causal inference methodsPublications or preprints related to predictive modelling

Please refer the Job description for details