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Computational Biologist - Deep Learning for Quantitative Tissue Analysis

Your function within the department

Your research environment
The research groups of Dr Hugo Horlings and Prof dr Lodewyk Wessels, are looking for a motivated and talented Computational Biologist to join their teams at the Netherlands Cancer Institute (NKI).
The Computational Pathology group of dr. Hugo Horlings focuses on quantifying and understanding tumor-immune interactions to predict immunotherapy response in cancer patients. We use and develop a variety of techniques on extracting genomic (e.g. RNA and Exome-sequencing) and proteomic data (e.g. in situ hydridization and multiplex immunohistochemistry) from large cohorts of patient derived archival material (formalin-fixed paraffin-embedded (FFPE)).
The Computational cancer biology group of Prof dr Lodewyk Wessels is focused on quantifying and understanding treatment response in model systems and patients. To this end we develop bespoke and novel computational methods focusing on data integration and tailored to new technologies. Both teams actively collaborate with many research groups in the NKI and strongly believe in the power of ‘team science’.
You will be embedded in the collaborative and enthusiastic international research groups of dr. Hugo Horlings and Prof. dr. Lodewyk Wessels, providing a unique environment that combines computational cancer biology with pathology and genomics-based translational research.

Your prospective project
With your expertise in computational life sciences and a very good understanding of image processing and deep learning, you will be responsible for quantitative image analysis of cellular heterogeneity based on images derived from H&E slides and multiplex immunohistochemistry. The goal of these analyses is to quantify the spatial characteristics (presence, position, distribution and relation to other cell types) of various (immune) cell types and to use these newly derived image features to 1) create a more comprehensive understanding of the relationship between these features and molecular characteristics of the tumor through integrative analyses and 2) to build better predictors of clinical endpoints such as response to therapy and outcome. To achieve this goal, you will follow both a knowledge-driven approach, where existing knowledge is employed to craft image features, as well as a deep learning approach, where the deep learning algorithms extract meaningful features in a data-driven fashion. In addition, you will also be working towards procedures to automate routine pathological diagnostics, an extremely data rich field where large gains can still be made. (Post-partum) breast cancer, and specifically association to outcome and immune therapy response will be areas of specific interest.

Your profile

We seek to recruit an ambitious postdoc, capable of independent thinking, with a strong commitment to translational research. Candidates should hold a degree in image processing, bioinformatics, computer science or a related discipline, have experience in machine learning (especially deep learning) and/or statistics, and be proficient in programming languages (e.g. R, Python). We expect candidates to be highly self-motivated, creative, and a team-player with strong communication skills. General background knowledge in biology and immunology is essential, and experience with projects involving the use of genomics and immune profiling data to identifying candidate targets and biomarkers is a plus.

Your career opportunities and terms of employment

You will join a dynamic international research group. You will collaborate with scientists and clinicians with expertise in different disciplines. You will have the opportunity to follow high-quality courses offered by the NKI postdoc career development program.
Your temporary employment will be for a period of 4 years. The gross salary per month will be from € 2.665,- to € 3.917,- according to the FWG-function group 55, and depends on previous experience. The terms of employment will be in accordance with the CAO Ziekenhuizen (Collective Labour Agreement for Hospitals).
Amsterdam is a very livable city with many cultural amenities. The institute is located within a 20 minute tram or bicycle ride from the center of Amsterdam and within 20 minutes from Schiphol airport by car, bus or bicycle.


For further information please visit our home pages: and or contact Hugo Horlings, Division of Diagnostic Oncology, or Lodewyk Wessels, Computational Cancer Biology,