Our lab develops and tests novel cancer treatments. We perform both fundamental and translational research and are currently conducting a prospective randomized clinical trial of dendritic cell based immunotherapy for melanoma patients (headed by Jolanda de Vries). Like for many immunotherapies, our earlier clinical data suggests that it substantially benefits some patients, but has no effect on others. A key challenge in this field is to identify patients who are likely to benefit from certain treatments. Due to the complexity of the interplay of immune system and cancer, such treatment selection is likely to require a multifaceted assessment of a patient's immune system state -- and this is where you come in.

Your task will be to design sound and robust methodology for exploiting diverse types of data -- including RNA-seq, flow cytometry, genetics, and tissue images -- for prognostic and predictive purposes. In this project you will employ in silico modeling (i.e., computer simulations) to study what we can and cannot infer from our data, and causal inference methodology to go hunt for genuine causal relationships instead mere correlations. The goal is to identify a subset of data that is valuable for diagnostic purposes, and test your methodology on the data of the trial we are running.

You will work in the lab's computational immunology unit headed by Johannes Textor, which is an integral part of the lab and therefore has direct access to all research and clinical data, and is directly involved in the design of experiments and trials. This provides you with an opportunity to make a direct, positive impact on bench and clinical research.                 

You should have a background in computer science, mathematics, physics, statistics or another quantitative discipline and have a strong interest in biology, or alternatively, a background in biology with a strong interest in computational methods and some preliminary experience in programing (e.g., R, matlab, python). You will also need good communication skills to function as a computational scientist in a biological lab.                

Fixed-term contract: 4 years.

• Salary is € 2266 gross per month in the first year up to a maximum of € 2903 gross per month in the last fourth year, plus additional vacation bonus (8% per year) and end of year payments (8.3% per year);
• This position is funded by KWF, the Dutch foundation for cancer research. The position is designed and funded as a 4-year full-time position, but part-time work (e.g., for accommodating childcare) can be negotiated. The position is available immediately and preferably the candidate should start by November 2017.
• Upon commencement of employment we require a certificate of conduct (Verklaring Omtrent het Gedrag, VOG). Radboud university medical center’s HR Department will apply for this certificate on your behalf.

Read more about the Radboudumc employment conditions.

Radboudumc (university medical center)

Radboudumc strives to be a leading developer of sustainable, innovative and affordable healthcare to improve the health and wellbeing of people and society in the Netherlands and beyond. This is the core of our mission: To have a significant impact on healthcare. To get a better picture of what this entails, check out our strategy film.

Our key strength is medical life-sciences and clinical practice, with an impressive infrastructure comprising state-of-the-art technology platforms and (translational) research facilities. The Radboudumc is therefore uniquely positioned in the emerging Euregio and Dutch healthcare infrastructure to play a leading role in the new healthcare paradigm of prediction, prevention and personalised medicine.

The Radboudumc focuses on scientific health challenges of today, with an eye on emerging diseases of the future.

Read more about what it means to work at Radboudumc and how you can do your part.

RIMLS
Radboud Institute for Molecular Life Sciences in the Netherlands is a leading European research school providing an outstanding research setting within the Radboud University Medical Center. The RIMLS focuses on basic science and its translation into pioneering treatments in the clinic. RIMLS innovations are advanced through technology platforms such as genomics, proteomics, and molecular imaging.
 
Tumor Immunologie
Research within the Department aims at a better understanding of our immune system using molecular-, cell biological- and immunological- techniques and is centered around antigen presenting dendritic cells which play an important role in regulating the immune response. An important activity of the Department is the translation of basic research into clinical application. In particular, research focusses on the development of novel dendritic cell based vaccines to treat cancer patients.