Open Positions


  1. Postdoc positions
  2. Student projects

Postdoc positions

Computational Tumor Immunologist: Single Cells to Clinical Response

The research groups of Dr Marleen Kok, Pia Kvistborg and Lodewyk Wessels, are looking for a motivated and talented Computational Biologist to join their teams at the Netherlands Cancer Institute (NKI).

The Projects

With your expertise in computational life sciences and a very good understanding of onco-immunology, you will be involved in the following projects:

  • Single T cell analyses: To study the state of T cells we are investigating tumor-specific T cell responses on the population level as well as on the single cell level using transcriptome analysis and high dimensional (30 parameter) flow cytometry. Using these data, we want to understand how T cell populations differ in their gene expression and functional state depending on their antigen specificity and their place in the immunodominance hierarchy.
  • Clinical systems Immunology: Using exome, TCR sequencing data, whole transcriptome and immunohistochemistry/immunofluorescence data of the tumor microenvironment as well comprehensive flow cytometry data of peripheral blood, we aim to better understand how immune checkpoint blockade—alone or in combination with chemotherapy—affects the breast tumor microenvironment. In parallel, systemic immune response characteristics will be studied. You will be a key player in a translational research team with clinicians and immunologists.

Your Profile

You are an ambitious, creative computational biologist, with a strong commitment to translational research. Candidates should hold a degree in bioinformatics, computer science or a related discipline, have experience in statistics and/or machine learning and be proficient in bioinformatics programming languages (e.g. R, Python). We expect candidates to be team-players 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.

The Research Groups

You will join the dynamic, international research groups of Pia Kvistborg, Marleen kok and Lodewyk Wessels. You will collaborate with scientists and clinicians with expertise in different disciplines.

The translational breast cancer immunology group of Dr Marleen Kok focuses on dissecting breast cancer-immune interactions, to optimize immunotherapy for breast cancer patients using novel combination treatments in clinical trials and the discovery of predictive biomarkers.

The T cell immunology group of Dr Pia Kvistborg focuses on understanding the state of tumor-specific T cells in cancer. We are currently investigating two aspects of the tumor-specific T cell response: 1) does the T cell state depend on which type of antigen the T cell is specific for (e.g. tumor-associated vs tumor-specific); and 2) what is the role of immunodominance in the development of the tumor-specific T cell response.

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. We actively collaborate with many research groups in the NKI and strongly believe in the power of ‘team science’.

Want More Information?

For further information please visit our home pages
Kvistborg group: https://www.nki.nl/divisions/molecular-oncology-immunology/kvistborg-p/
Computational Cancer Biology: http://ccb.nki.nl/

or contact

Pia Kvistborg, p.kvistborg@nki.nl or
Marleen Kok, m.kok@nki.nl, or
Lodewyk Wessels, l.wessels@nki.nl

Computational Biologist: Tumor Immunology

Your role within the department

The research groups of Dr Karin de Visser, dr Marleen Kok 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 Inflammation and Cancer group of dr. Karin de Visser is studying the impact of the immune system on metastatic breast cancer utilizing sophisticated mouse tumor models and state-of-the art ex vivo and in vitro immunological and molecular assays. The lab of de Visser closely collaborates with the translational research group of medical oncologist dr Marleen Kok. The mission of this team is to discover novel mechanisms underlying the crosstalk between breast cancer and the immune system, to optimize immunotherapy for breast cancer patients using novel combination treatments in clinical trials and the discovery of predictive biomarkers.

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. We actively collaborate with many research groups in the NKI and strongly believe in the power of ‘team science’.

With your expertise in computational life sciences and a very good understanding of onco-immunology, you will be involved in the following projects:

  • Mouse models for metastatic escape from immune control. To study the causal relationship between immune cells and metastatic breast cancer, we utilize state-of-the art genetically engineered mouse tumor models. We have extensive RNA-sequencing datasets of isolated immune cell populations, as well as RNA-sequencing and exome sequencing data of primary breast tumors and organ-specific metastases from these mouse models. You will be responsible for the computational analyses of the data, and to extract candidate pathways/genes from these datasets that can subsequently be tested in follow up experiments in the lab. Moreover, you will link these pre-clinical data to human datasets.
  • Systemic and intra-tumoral immunomonitoring for precision immune-modulation. We are performing extensive immunomonitoring studies in human breast cancer patients treated with immune checkpoint blockade, with the ultimate aim to validate hypotheses derived from our preclinical research in human cancer patients, and to stratify breast cancer patients for immunomodulatory therapies. We are setting-up multiplex immunohistochemistry with antibody panels that audit intratumoral lymphoid and myeloid cell populations and their functional state. In parallel, we have established an extensive multiplex flow cytometry pipeline to monitor the systemic immune landscape of breast cancer patients and healthy controls. These analyses generate a substantial amount of data which require thorough computational analyses.
  • Mapping Immuno-genomic interactions. We are interested in dissecting the impact of the genetic make-up of breast tumors on the intra-tumoral and systemic immune landscape. You will be responsible for the identification and validation of genotype-immunophenotype associations by connecting DNA exome sequencing data, RNA sequencing data and immune profiles derived from our mouse tumor models and cancer patients. You will use both publicly available datasets and newly generated datasets.

You will be embedded in the collaborative and enthusiastic international research groups of dr. Karin de Visser, dr Marleen Kok and Prof. dr. Lodewyk Wessels, providing a unique environment that combines computational cancer biology with pre-clinical and translational research into immune-oncology.

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 bioinformatics, computer science or a related discipline, have experience in statistics and/or machine learning and be proficient in bioinformatics 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 € 3.363,- to € 3.774,- 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.

Want more information?

For further information please visit our home pages:
https://www.nki.nl/divisions/tumor-biology-immunology/de-visser-k-group/
https://www.nki.nl/divisions/molecular-carcinogenesis/wessels-l-group/
or contact Karin de Visser, division of Tumor Biology & Immunology, k.d.visser@nki.nl, Marleen Kok, medical oncologist, m.kok@nki.nl, or Lodewyk Wessels, Computational Cancer Biology, l.wessels@nki.nl.

 

Bachelor / Master student project: Assessing tumor heterogeneity in silico

Background

Tumors originate from cells that have accumulated genetic mutations. Subsequently, tumors evolve over time, leading to genetically distinct subpopulations of cells within a single tumor. This so-called intra-tumor heterogeneity (ITH) poses several challenges in cancer research and therapy: How to treat such heterogeneous mixtures of cells? How to target at best all of them? The more heterogeneous a cancer, the higher it’s chance to ‘escape’ a treatment? If we know the path of tumor evolution, can we stop it?

cancer_evolution_heterogeneity

Challenges

Many bioinformatics tools have been developed that try to quantify ITH and/or to reconstruct the tumor’s evolution based on copy number changes, mutations and other information from DNA sequencing data. This project involves a literature search to catalogue applicable tools and their requirements, and subsequently installing and benchmarking a selection of tools on real clinical samples and in silico simulated data. The clinical data comprises multiple sequencing files from a small number of patients, for instance from different tumor locations or before and after treatment. The simulated data would involve mixing samples from different patients in various ratios to mimic cell populations. In addition, TCGA data can be used to validate methods on a large scale.

Project description

The project is in close collaboration with both the department of Pathology and the Computational Cancer Biology group at the Netherlands Cancer Institute (NKI) in Amsterdam. As an end product, we hope to have a pipeline that can be used in multiple research projects and can be run routinely on new clinical samples. Potential findings in our clinical samples can be included in a scientific publication. Experience with working in a Unix environment / command-line programming is a big plus, but not a strict requirement. For more information, please contact Marlous Hoogstraat.