[BBC] COMPUTATIONAL BIOLOGIST - TUMOR IMMUNOLOGY

Lodewyk Wessels l.wessels at nki.nl
Thu Mar 29 10:05:18 CEST 2018


VACANCY COMPUTATIONAL BIOLOGIST - TUMOR IMMUNOLOGY


YOUR ROLE WITHIN THE INSTITUTE

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'.


PROJECTS

You will be involved in the following projects: 

1. 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.    

2. 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. 

3. 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.


WANT MORE INFORMATION?

Please visit our home pages 
https://www.nki.nl/divisions/tumor-biology-immunology/de-visser-k-group/
https://ccb.nki.nl

or contact 
Karin de Visser: k.d.visser at nki.nl
Marleen Kok: m.kok at nki.nl 
Lodewyk Wessels: l.wessels at nki.nl

 



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