Hi all, Still 1 week to apply for the positon in the Computational Cancer Biology group at NKI in Amsterdam. Have a nice day, Magali Integrative modelling to identify therapy resistance mechanisms Project description The purpose of this project is to identify the underlying resistance mechanisms in invasive lobular carcinoma (ILC). ILCs are known as ‘slow killers’ as they grow relatively slowly, but respond poorly to therapy, eventually killing the patient. To unravel the resistance mechanisms, we have generated comprehensive molecular profiles (gene expression, mutational, copy number and (phospho-)proteomics profiles) from matched pairs of sensitive and resistant mouse models of ILCs. We will employ integrative computational (Bayesian) modeling to integrate prior knowledge and the molecular datasets to identify candidate resistance factors. These will be validated in genetic and pharmacological perturbation studies in cultured ILC cell lines and mouse models. Knowledge of these mechanisms will enable us to design combination therapies able to block the development of resistance, leading to improved therapy response. The successful candidate will be responsible for carrying out all the computational analyses, including the complete analysis workflow starting at the basic analyses of the DNA and RNA sequencing and mass spectrometry data up to the more complicated integrative analyses and the Bayesian pathway modelling. He/She will also be expected to coordinate the project and to liaise with the molecular biologists, the animal facility, the genomics core facility and the proteomics facility. The project will be carries out in close collaboration with the groups of Jos Jonkers (mouse models of breast cancer) and Maarten Altelaar (proteomics). Candidate profile We are seeking highly motivated Postdoc or PhD candidates with a degree in bioinformatics, computer science or a related discipline. Applicants should be experienced in cancer biology and clinical applications and should be skilled in analysing high-throughput molecular data. Experience in analyses of (phospho)-proteomics data is a plus. The candidate needs to be proficient in common bioinformatics scripting and programming languages (e.g. R, Python). Interested? Please send CV and motivation letter to Magali Michaut (m.michaut@nki.nl<mailto:m.michaut@nki.nl>) & Lodewyk Wessels (l.wessels@nki.nl<mailto:l.wessels@nki.nl>). Please include a list of publications and the names and contact information of at least two references. See ccb.nki.nl<http://ccb.nki.nl> for further information. Deadline 1 June 2016