招聘簡介：

　　合同期限：3年

　　Petsalaki小組研究人類細胞信號傳遞，旨在了解在不同環境、組織和條件下控制不同細胞反應的因素。我們分析和整合不同的“組學”數據集（重點是磷蛋白組學和蛋白質組學），以提取和比較上下文特定的信號網絡。更多信息請訪問：Petsalaki

　　Zaugg小組調查了個體間分子表型的變化及其遺傳和表觀遺傳變異，目的是更好地了解復雜遺傳疾病的分子基礎和個體間藥物反應的差異。我們在計算調控基因組學、轉錄組學和數據整合方面擁有強大的專業知識。更多信息請訪問：Zaugg

　　英文原文：

　　Contract Duration: 3 years

　　The Petsalaki group studies human cell signalling with the aim to understand what controls different cell responses in different environments, tissues and conditions. We analyse and integrate diverse 'omics' datasets (with emphasis on phosphoproteomics and proteomics), to extract and compare context-specific signalling networks. More info at: Petsalaki

　　The Zaugg group investigates the variation of molecular phenotypes among individuals along with their genetic and epigenetic variation with the aim of better understanding the molecular basis of complex genetic diseases and inter-individual differences in drug response. We have strong expertise in computational regulatory genomics, transcriptomics and data integration. More info at: Zaugg

　　Your role

　　Combination therapies aimed at inhibiting multiple targets or cancer pathways can combat resistance and exploit new actionable dependencies in defined genetic contexts. The candidate will work as part of collaborative team to unlock the potential of rational target/pathway combinations in oncology through ambitious integrative network biology and large-scale functional genomics screens.

　　You will handle very large and diverse omics datasets, ranging from genomics to phosphoproteomics, as well as CRIPSR perturbation data. You will integrate such data and analyse it using advanced statistical approaches, as well as network modelling to identify cell network rewiring upon perturbation and predict combination targets. You are expected to work independently and will be the main driver of the project. You will be employed at EMBL-EBI as part of the Petsalaki group and have a joint appointment with the Zaugg group at EMBL Heidelberg. In addition, you will work tightly with the members of the collaborative project that also includes the team headed by Mathew Garnett at the Sanger institute.

　　This project is funded by Open Targets which is a public-private partnership that uses human genetics and genomics data for systematic drug target identification and prioritisation. This project will involve scientific teams from the Sanger Institute, European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory (EMBL) and multiple pharmaceutical companies working collaboratively to develop new combination therapies for cancer.

　　You have

　　Strong background and skills in large scale data analysis preferably using biological data

　　Excellent knowledge of advanced statistics

　　Excellent ability to communicate in written and oral English and work in a team

　　Excellent programming skills preferably in python and R

　　High enthusiasm for mining data for generating biological hypotheses

　　You might also have

　　The skills below are not necessary but would be an asset:

　　Experience in network modelling

　　Background knowledge in epigenetics, gene regulatory networks and/or cell signalling

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