PhD student in data science focusing on federated learning applied to healthcare at the Clinical...

Updated: about 1 month ago
Job Type: Temporary
Deadline: 01 Nov 2020

Maastricht University has a vacancy for a PhD student at the faculty of Health Medicine and Life Sciences in the Clinical Data Science group. At the Clinical Data Science group, we work on three main research areas: building global data sharing infrastructures; applying machine learning to build models from these data; and, using these models to improve healthcare.

The PhD position is embedded in the novel Netherlands Consortium of Dementia Cohorts , a unique project to unravel the aetiology of dementia in order to find clues for primary prevention by performing pooled analyses of 9 ongoing prospective cohort studies on cognitive aging and dementia from the Netherlands. 

In this project, the successful candidate will be responsible for implementing federated learning infrastructure and developing federated algorithms. Federated learning has attracted the attention of major AI players like Google and Nvidia because it provides a workaround to the growing ethical and legal barriers to data sharing. Federated learning has the potential to play a key role in the next few years in the evolution of privacy-conscious, data-hungry AI, as shown by the fact that major AI conferences (e.g. Neurips, ICML) are already holding workshops dedicated to it.

The successful candidate will also be in charge of data harmonization pipelines to make research data comply FAIR data principles. In addition to this project, the successful candidate will have the opportunity to apply statistical and machine learning techniques to a range of clinical problems.

The successful candidate will join a cross-faculty team consisting of computer scientists, medical physicists and medical informaticians, PhD students, software engineers and post-doctoral researchers.


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