The research aims at helping people with rheumatic autoimmune disorders and improving healthcare with your data mining and classification skills!

Rheumatic diseases are (still) mostly incurable autoimmune diseases. They arise from a complex interaction between genetics and environment. If the diseases are recognized earlier and better classified, we can improve care and increase knowledge about underlying disease pathology.

Our data science rheumatology group focuses on the following four research subjects:

·         Subgroup identification through high dimensional pattern recognition

·         Developing eHealth tools to improve healthcare systems for rapid diagnosis and optimal medication selection

·         Identification of causal factors in disease development (genetic and environmental factors)

·         Coordinating (federated) machine learning analyses within European partnerships working on applications of AI for (pre)clinical research

For this we use high-throughput computational techniques on big data (electronic health records and genetics) for pattern recognition and classification. We have at our disposal a unique set of online acquired symptom questionnaires (>20,000 participants), electronic patient files (>25,000 patients), European non-public datasets and public databases with medical data, laboratory values ​​and genetics

·         You have graduated (university) in a data science study (e.g. bioinformatics, technical medicine, clinical technology, statistics, epidemiology, computer science or data science) or have demonstrable data science skills in addition to a medical study (such as but not limited to medicine, and public health management);

·         Furthermore, you are motivated and committed to expanding your skills and making them clinically relevant;

·         Finally you can strengthen our team in the areas of:

-          Unsupervised clustering and natural language profiling

-          Predictive algorithm development through supervised machine learning

-          Federated learning and manifold alignment

-          Genetics

-          Causal inference

Since we are searching for multiple candidates for different projects, we can tailor the PhD trajectory to your specific skills and interests.

Fixed-term contract: 4 years.

You will be given an employment contract for the production of a PhD thesis for the duration of the program with a maximum of four years. The salary amounts to € 2,789 gross per month in the first year, up to a maximum of € 3,536 in the last year with fulltime employment (scale Pro, CLA UMC).

LUMC

At the Leiden University Medical Center, we continuously work on improving patient care. We invest in groundbreaking, international research and work with the latest equipment. Together with our team of doctors, medical specialists, teachers, academic researchers and supporting staff, we aim for the best quality in health care, education and international research. And we need you to realize our goals!

rheumatology data science lab

You will be part of the rheumatology data science lab led by Rachel Knevel M.D. Ph.D. We are a closely collaborating research group where everyone's work is linked to the work of others. In this lab we develop various tools for data analysis. We are affiliated with the Leiden Computational Biology Center (LCBC), a group of data scientists embedded within the LUMC and Delft University of Technology (Pattern recognition & bioinformatics).

The lab is part of the Rheumatology department, an EULAR Center of Excellence, where, in addition to clinical care, a great deal of research is conducted into the pathogenesis of various autoimmune diseases. The rheumatology department consists of approximately 100 enthusiastic postdocs, PhD candidates, research analysts, physicians and support staff.

The research and the PhD trajectories are carried out in collaboration with and under the co-supervision of:

-          Computational biology, Prof. Marcel Reinder, Dr. ir. Erik van Akker

-          Clinical epidemiology, Prof. Saskia le Cessie

-          Medical decision making, Prof. Ewout Steyerberg

-          Rheumatology, Prof. Tom Huizinga

To guarantee good supervision and to optimize integration of projects, we have weekly lab meetings, weekly one-on-one meetings and monthly multidisciplinary meetings