BIOINFORMATICIAN POSITION EARLY DETECTION OF OVARIAN CANCER and INTEGRATION OF TISSUE SPATIAL MAPS AND GENE EXPRESSION The research groups of Lodewyk Wessels, Frederic Amant and Christianne Lok are looking for a motivated and talented Computational Biologist to join their teams at the Netherlands Cancer Institute (NKI). PROJECT DESCRIPTIONS. Early detection of Ovarian cancer. Differentiation between benign growth and ovarian tumors before surgery is currently far from optimal. This leads to a significant fraction of ovarian tumors going undetected and also a large fraction of benign growths being unnecessarily treated in specialized settings. In this project we will be employing innovative non-invasive sampling of peripheral blood to develop a more accurate test for the detection of ovarian tumors. We will employ two strategies. First we will isolate and perform RNAseq profiling on tumor educated platelets (TEP). Second, we will perform DNA sequencing and to detect abnormal DNA copy number profiles from the circulating tumor DNA (ctDNA). For both datasets, the successful candidate will build classifiers to accurately distinguish ovarian cancer from benign growths. Integration of gene expression and tissue imaging to study post-partum breast cancer. Breast cancers that occur 1 to 2 years after childbirth (postpartum breast cancer) have a particularly poor outcome. It has been hypothesized that (immunological) changes in the breast, occurring after childbirth, are underlying the poor prognosis of postpartum breast cancer. In this project we will investigate postpartum breast cancer by combining two unique data sets across 400 patients. Tumors will be subjected to RNA-sequencing as well as spatial tissue profiling for a panel of immune markers employing the VECTRA technology. The spatial profiling provides the location of cells in a cross section of the tumor as well as the expression of the recorded markers in each cell. This allows a detailed characterization of the tumor and the surrounding stroma, indicating which cells occur in the stroma, their position with respect to each other and with respect to the tumor cells. The successful candidate will perform computational analysis of these datasets separately and in an integrated fashion to study the mechanisms that underlie postpartum breast cancer. CANDIDATE PROFILE. We are seeking a highly motivated bioinformatician with: • A degree in bioinformatics, computer science or a related discipline • Experience with high-throughput data analysis, especially sequencing data • Proficiency in bioinformatics programming languages (e.g. R, Python) • Good cross-disciplinary collaborative and communication skills • Experience in statistics, machine learning and/or image processing is a plus • Experience in cancer biology and clinical applications is a plus INTERESTED? Please send CV and motivation letter to Lodewyk Wessels (l.wessels@nki.nl) and Patty Lagerweij (p.lagerweij@nki.nl). Please include the names and contact information of at least two references. For further information on the Wessels group (Computational Cancer Biology) please visit our home page https://ccb.nki.nl/