The genome diagnostics division of the department of genetics is one of the front-runners in the implementation of novel genetic technologies for improving patient diagnostics. In particular, Exome (WES) and whole genome sequencing (WGS) are currently implemented for genetic testing of more than 7000 patients with genetic diseases per year. In order to obtain a genetic diagnosis these data are interpreted by a laboratory specialist using a wide-variety of information of the patient phenotype, known disease genes, and the genetic profile of the patient. However, this (1) requires a substantial amount of time from the specialist, which (2) results in large turn-around times for these tests and (3) these analyses are prone to human error. The Artificial Intelligence department aims at automating such procedures using machine learning techniques. In particular, the department specializes in the construction of novel algorithms that provide Bayesian probabilistic predictions, based on the integration of multiple large-scale data modalities.
We are looking for a PhD candidate who combines expertise in the field of genetics and artificial intelligence and is able integrate this wealth of available data in order to automatically diagnose patients with genetic diseases.
Additional information about the research group and publications can be found here:
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