PhD student in Decision Support Systems using Big Data.

Job description

Maastricht University has a vacancy for a PhD student at the faculty of Health Medicine and Life Sciences in the department of Radiation Oncology (MAASTRO). MAASTRO’s strategic goal is to tailor cancer treatments to the clinical, biological and genetic characteristics of an individual patient so that the best outcome can be achieved. An important part of MAASTRO’s strategy is the research line Radiomics where "machine learning" techniques are applied for knowledge discovery from large imaging datasets (http://www.radiomics.org).

Together with partners Tata Memorial Centre, C-DAC and Philips in India and ptTheragnostic in The Netherlands, MAASTRO has received NWO IndoDutch funding for a 4 year research project called BIONIC (Big Imaging data approach for Oncology in a Netherlands India Collaboration).

The general aim of this NWO IndoDutch BIONIC is to unite academic, industrial and clinical leaders to improve cancer care using a Big Data approach for medical imaging. Vast amounts of patient image data from top cancer centers in the Netherlands and India will be used, in a privacy preserving manner, to develop Decision support systems. We will prove that use of these decision support systems will lead to better treatment decisions.



In this project, you will be member of an international team of physicians, physicist, computer scientists and software engineers who jointly develop Big Data technology to open up petabytes of medical imaging data stored in hospitals worldwide and use it to learn of decision support systems for cancer treatments.

Specifically, you will develop and deploy the technology to learn and validate predictive models for lung, cervical, head&neck and rectal cancer patients. You will build on existing models developed by the group and extend these with Radiomics features to improve their performance accuracy in the prediction of survival, tumor control and toxicities. You will do this work in a privacy preserving manner where no data needs to leave the individual hospital so that privacy maximally preserved. Challenges regarding data quality and interoperability between centres in The Netherlands and India as well as the mathematical challenges of learning models without “seeing” the data will be addressed by you in a team setting.

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