Vacancies
Currently we have the following job offerings:
Computational biology positions: NGS for personalized medicine
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Project outline
Genetic alterations are major determinant of responses to (targeted) therapies in cancer. To gain insight into resistance mechanisms to therapy and thus better tailor treatment, genetic and response characterization for large panels of tumors are required. The Center for Personalized Cancer Treatment (CPCT) is a collaboration between the University Medical Center Utrecht, The Erasmus Medical Center Rotterdam and The Netherlands Cancer Institute Amsterdam, aimed at collecting and characterizing such cohorts. By the end of this year we will have collected and sequenced a total of 1500 tumor and normal samples. The successful candidates will work closely with biologists and clinicians to develop computational approaches that characterize the mutational landscape of these cancers with specific emphasis on the impact this landscape has on therapy response. To this end the candidate will have proprietary access to data from the Sanger Cell line panel (www.cancerRxgene.org). The goal is to integrate this database with the tumor exome and response data to bring personalized medicine a step closed to the clinic.
Candidate Requirements – Education and Experience
We are seeking highly motivated Postdoc or PhD candidates with a degree in bioinformatics, computer science, mathematics or physics and with a strong cancer biology interest. Preferably applicants should have a strong documented experience in analyzing high-throughput sequencing data. In addition, we value experience in one or more of the following: sequence analysis, clinical data analysis, gene expression analysis, machine learning or applied statistics. The candidate needs to be proficient in programming languages such as Java, Perl or Python, and be comfortable with Linux systems. Fluency in spoken and written English is a strong requirement
Location
The project will employ the complementary expertise and tools of four groups participating in the Center for Personalized Cancer Treatment: Edwin Cuppen and Emile Voest at the University Medical Center Utrecht and Rene Bernards (Molecular Carcinogenesis) and Lodewyk Wessels (Computational Biology) at the Netherlands Cancer Institute, Amsterdam. The position is primarily embedded within the Bioinformatics and Statistics Group (Wessels) (bioinformatics.nki.nl) at the Netherlands Cancer Institute, Amsterdam.
Contact details
Please contact Dr. Lodewyk Wessels, tel. +31 20 512 7987 or e-mail: l.wessels@nki.nl. When applying please ensure you include a CV, list of publications and the names and addresses of at least two persons that can be approached as references. Also see bioinformatics.nki.nl for further information.
Closing date
3 February 2013
Integrative computational analysis of Androgen Receptor genomics to predict outcome and therapy response
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Project outline
Prostate cancer is one of the most prevalent cancers in males. Currently, Gleason grade, TNM stage, surgical margin status and serum PSA levels are used as prognostic markers in prostate cancer. Although these markers may predict survival and recurrence after radical prostatectomy, they are not suitable for selecting patients for further therapeutic interventions. In this project, we aim to identify predictors of prostate cancer recurrence and response to Androgen Deprivation Therapy. We will generate the most comprehensive overview of primary prostate cancer genomics, including Androgen Receptor/chromatin binding patterns, histone modifications, gene expression and copy number data derived from primary prostate tumor samples, prostate tumor samples that have become resistant to treatment as well as and prostate cancer cell lines. The successful candidates will work closely with biologists and clinicians to develop computational approaches that integrate all these data streams to arrive at improved predictors of recurrence and therapy response.
Candidate Requirements – Education and Experience
We are seeking highly motivated Postdoc or PhD candidates with a degree in bioinformatics, computer science, mathematics or physics and with a strong cancer biology interest. Preferably applicants should have a strong documented experience in analyzing ChIP sequencing and gene expression data. In addition, we value experience in one or more of the following: sequence motif analysis, clinical data analysis, gene expression analysis, machine learning or applied statistics. The candidate needs to be proficient in programming languages such as Java, Perl or Python, and be comfortable with Linux systems. Fluency in spoken and written English is a strong requirement.
Location
The project involves a consortium consisting of the NKI-AVL and the Erasmus MC and will mainly employ the complementary expertise and of the groups of Andre Bergman (Molecular Genetics and Internal Medicine), Wilbert Zwart (Molecular Pathology) and Lodewyk Wessels (Computational Biology) at the Netherlands Cancer Institute, Amsterdam.
Contact details
Please contact Dr. Lodewyk Wessels, tel. +31 20 512 7987 or e-mail: l.wessels@nki.nl., or Dr Wilbert Zwart, tel +31 512 7920 or e-mail: w.zwart@nki.nl When applying please ensure you include a CV, list of publications and the names and addresses of at least two persons that can be approached as references. Also see bioinformatics.nki.nl for further information.
Closing date
3 February 2013
Comprehensive computational modeling for combination treatment design
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Project outline
All cancers arise due to alterations in their genomes. Although insight into the genetic lesions in tumors by genome sequencing does already assist in selecting some drug regimens, it rarely results in disease eradication due to the emergence of drug-resistance. More sophisticated combination therapies in which several oncogenic pathways are targeted simultaneously could alleviate this problem. However, at present we are unable to extract and interpret the necessary information from tumors to predict which drug regimen will be most adequate. In this project we will collaborate with Welcome Trust Sanger Center and employ the 1000 cancer cell line data set to tackle this problem. This data set comprises large-scale molecular characterization and cancer drug screening of all cell lines for 400 anti-cancer drugs. The molecular data currently consists of gene expression, copy number (SNP-6), and whole exome sequencing data and is being expanded. The successful candidate will work closely with scientists at the Welcome Trust Sanger Center and the Netherlands Cancer Institute and employ computational approaches to mine this rich, valuable pre-clinical resource. Potential results include 1) new molecular biomarkers to identify sensitive populations 2) repositioning of existing drugs in other tumor types and 3) potential drug combinations aimed at overcoming resistance mechanisms. Hypotheses emerging from these analyses will be validated in model systems and where possible in clinical settings.
Candidate Requirements – Education and Experience
We are seeking highly motivated Postdoc or PhD candidates with a degree in bioinformatics, computer science, mathematics or physics and with a strong cancer biology interest. Preferably applicants should have a documented experience in analyzing high-throughput genomic data. The candidate needs to be proficient in common bioinformatics scripting and programming languages. Fluency in spoken and written English is a strong requirement.
Location
The project involves groups at the Netherlands Cancer Institute, Amsterdam (Rene Bernards, Molecular Carcinogenesis, and Lodewyk Wessels, Computational Biology) and the Welcome Trust Sanger Institute (Mathew Garnet and Ultan McDermott, Cancer Genome Project). This position will be embedded in the Computational Biology Group lead by Lodewyk Wessels.
Contact details
Please contact Lodewyk Wessels, tel. +31 20 512 7987 or e-mail: l.wessels@nki.nl. When applying, please ensure you include a CV, list of publications and the names and addresses of at least two persons that can be approached as references. Also see bioinformatics.nki.nl for further information.
Closing date
3 February 2013