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PostDoc/PhD student Computational Oncogenomics

Your function within the department

The research group of Reuven Agami at the division of Oncogenomics aims at the identification and preclinical characterization of novel cellular vulnerabilities that can be exploited to combat resistant cancer. For this purpose, we develop innovative genomic and genetic tools. Key targets and processes are mRNA translation, non-coding RNAs, enhancers, and chromatin modulators.

In particular, we employ novel unbiased functional genetic screening approaches (based on own CRISPR and RNAi tools), perform thorough mechanistic studies to understand their connection with the cancerous phenotype, and use this information for the development of innovative cancer therapeutic approaches. Towards this end, we combine advanced bioinformatics, genomics and experimental approaches. 

This position starts with close collaboration with a very experienced bioinformatician postdoc, evolving into being an independent researcher and in cooperation with various molecular biologists - members of our team. You will focus on novel approaches to study genetic events associated with chromatin structure-function.

Your profile

We seek to recruit an ambitious PostDoc/PhD student, capable of independent thinking, with a strong commitment to science, and a solid experience in molecular biology. In particular, past experience with various aspects of RNA biology or metabolic processes in human cancer is required. General knowledge about functional screening with RNAi and CRISPR tools and epigenetics is an advantage, as well as basic bioinformatics knowledge. We expect the candidate to be highly self-motivated, creative, and able to work in a team.

The skills required includes, but not limited to:
1. Experience with NGS (RNA and DNA based) data analytical approaches, tools and techniques.
2. Programming experience in either of the two- PERL and Python, SHELL scripting.
3. Statistical programming in R (including bioconductor), data representation and visualization, statistics etc.
4. Understanding of genomics protocols and ability to communicate with wet-lab researchers.

Addition plus points:
1. Experience of LIMS and sequencing platforms.
2. Experience with Mass-spectrometry data analysis.
3. Experience with machine learning (SVM, HMM, Random Forest etc), data clustering (PCA, tSNE) and other large-scale data sorting approaches.
4. Experience with single cell genomics is plus.
5. Publication experience in international journals.

Your career opportunities and terms of employment

You will join an international research team in a stimulating and interactive research environment. You will have access to unique data coming from our experiments.
1.You will have the opportunity to follow high-quality courses offered. In case of a postdoc position, you will follow by the NKI postdoc career development program. In case of a PhD position you will participate in the education program of the Oncology Graduate School (OOA) Amsterdam.
2. our temporary employment will be for a period of 5 years. We offer a competitive salary (including possibilities for additional tax-reduction) and if necessary at the beginning temporary housing facilities in the vicinity of the institute. For a postdoc, 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. In case of a PhD position, the gross salary per month will be from € 2.665,- € 3.282, according to the standard PhD scales. The terms of employment will be in accordance with the CAO Ziekenhuizen (Collective Labour Agreement for Hospitals).

For further information please visit our institutional home page
(, our lab website (, or  directly contact Prof. Reuven Agami at tel. +31 20 5122079 or e-mail:

When applying please include a list of your publications and the contact details of 2 referees.

Selected recent publications: 
Loayza-Puch, F., K. Rooijers, L.C. Buil, J. Zijlstra, J.F. Oude Vrielink, R. Lopes, A.P. Ugalde, P. van Breugel, I. Hofland, J. Wesseling, O. van Tellingen, A. Bex, and R. Agami, Tumour-specific proline vulnerability uncovered by differential ribosome codon reading. Nature, 2016. 530(7591): p. 490-4.
Korkmaz, G., R. Lopes, A. P. Ugalde, E. Nevedomskaya, R. Han, K. Myacheva, W. Zwart, R. Elkon and R. Agami (2016). "Functional genetic screens for enhancer elements in the human genome using CRISPR-Cas9." Nat Biotechnol 34(2): 192-198.
Slobodin, B., R. Han, V. Calderone, J.A. Vrielink, F. Loayza-Puch, R. Elkon, and R. Agami, Transcription Impacts the Efficiency of mRNA Translation via Co-transcriptional N6-adenosine Methylation. Cell, 2017. 169(2): p. 326-337 e12.