Project Description
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 intepreted independently by a trained technician and a laboratory specialist using a wide-variety of information of the patient phenotype, known disease genes, and the genetic profile of the patient. This is a cumbersome process that can take up to weeks. The Radboudumc Department of Genetics has exome sequencing data of more than 30,000 individuals, stored as more than 500Tb of data.
We propose to develop an AI-based learning algorithm, that integrates all of this information and is able to automatically diagnose patients with genetic diseases. This will reduce (1) the amount of time spent on interpretation, and thereby also (2) reduce turn-around times for these tests, and (3) will improve diagnoses by reducing the risk of human error.
Requirements
We are looking for an ambitious, creative and enthusiastic computer scientist, biomedical engineer or data scientist. You should have a MSc degree in a relevant field, skills in developing artifical intelligence systems and text analysis. Good communication skills and programming experience, preferably in Python/C++, are essential.
Terms of employment
You will be appointed as a PhD student for four years with the standard salary and secondary conditions for PhD students in the Netherlands. Your performance will be evaluated after 1 year. The research should result in a PhD thesis and a system that will be implemented in Radboudumc.
Application
You can already apply directly by e-mail to Dr. Christian Gillissen. In your application include a motivation letter, your CV, list of grades and links to publications and your Master thesis or other work you have written in English.
All applications will be processed immediately upon receipt until the position has been filled.
