THE POSITION We are looking for a highly motivated candidate for a PhD project in Computational Oncology at the department of Biomedical Data Sciences. This project focusses on modelling tumor heterogeneity and discerning drivers of clonal evolution and therapy resistance by analyzing single-cell data on material derived from patients with acute myeloid leukemia. IN SHORT • You will work on integrative computational methods to discern, characterize and trace different clonal lines present within tumors • You will work in a multi-disciplinary environment ranging from data science to translational oncology within the recently established Leiden Center for Computational Oncology • You will disseminate your work by writing scientific manuscripts and presenting your research at international conferences. The combination of this work will lead to a PhD title WHAT YOU WILL DO Acute myeloid leukemia (AML) is a cancer of the myeloid immune lineage and represents about 1.2% of all new cancer cases. AML typically affects elderly patients, with only 5-15% of the patients above age 60 achieving a durable remission. Promising treatments are steadily released, with yet unknown resistance mechanisms. Hence, within this project, you will conduct integrative analyses using various types of single-cell molecular data sources to identify mechanisms driving clonal evolution and therapy resistance. Within the newly established Leiden Center for Computational Oncology, acute myeloid leukemia was chosen as one of the projects to spearhead the development of novel computational tools that provide more insight into tumor heterogeneity and tumor evolution under therapeutic pressure. The activities of the PhD candidate are purely computational and will be embedded within the Leiden Computational Biology Center (prof. M. Reinders), and the department of Hematology (prof. H. Veelken, MD). WHAT WE ASK You hold a MSc degree in Bioinformatics, Statistics, Life Sciences, or a similar area. You possess a strong background in data analytics, have hands-on experience with applying machine learning methods, and you are familiar with scripting languages such as R or Python. Knowledge of genetic analyzation and transcriptomic studies are favored but not required. You enjoy the pursuit of knowledge across multiple field, and you have an optimistic and kind nature. INTERESTED? Please send your CV and motivation letter (deadline November 15th) to: https://lumc.recruitee.com/l/en/o/phd-candidate-tumor-heterogeneity-in-acute... Kind regards, Erik van den Akker Leiden University Medical Centre Molecular Epidemiology <http://www.molepi.nl/en/people/people_item/t/erik_van_den_akker> Einthovenweg 20, 2333 ZC, Leiden, The Netherlands Building 2 [Research], Room S5-38 tel: +31 (0)71 526 85 57 Delft University of Technology Delft Bioinformatics Lab <https://www.tudelft.nl/ewi/over-de-faculteit/afdelingen/intelligent-systems/pattern-recognition-bioinformatics/the-delft-bioinformatics-lab/> Van Mourik Broekmanweg 6, 2628 XE, Delft, The Netherlands Building 28 [WI], Room W5.820 tel: +31 (0)15 278 55 17