招聘简介：

博士后研究员

炎症研究中心

33199英镑-39609pa英镑-固定期限至2021年12月31日

爱丁堡大学，代谢组学和单细胞RNA测序综合多组学分析的计算生物学家。

我们正在招募一位积极性很高的博士后研究员，他将专注于在代谢组学和单细胞RNA测序的综合多组学分析领域的前沿计算方法的应用和发展。成功的候选人将加入冯博士在炎症研究中心（CIR）的小组，并将与位于遗传学和分子医学研究所（IGM）的庞汀教授小组和化学学院坎贝尔博士小组密切联系。

Feng实验室开发了一种斑马鱼模型，用于活体内肿瘤前细胞（PNC）的活体成像和基因分析。该实验室的目标之一是通过使用scrnaseq分析充分描述谱系发育和细胞-细胞相互作用网络的细节，来剖析调节宿主细胞如何与其生态位中初始PNC相互作用的机制。单细胞RNaseq数据也将与完整斑马鱼PNC生态位上成像质谱（IMS）生成的代谢组学数据整合。

理想的候选者将有很强的计算背景，他们渴望在单细胞转录组学快速移动的领域中发展自己的技能和知识，渴望探索和建立集成多组学分析的新计算方法。你将应用和发展计算方法，综合分析单细胞转录组与代谢组学，以允许发现和询问细胞亚群和细胞功能状态在肿瘤开始。

优秀的沟通技巧和探索计算生物学和实验生物学之间的接口的真正热情是必不可少的。

英文原文：

Postdoctoral Research Fellow

Centre for Inflammation Research

£33,199 – £39,609pa – fixed term until 31st December 2021

The University of Edinburgh, Computational Biologist in integrated multi-omic analysis of metabolomics and single cell RNA sequencing.

We are recruiting a highly motivated post-doctoral researcher who will focus on the application and development of cutting-edge computational methods in the area of integrated multi-Omic analysis of metabolomics and single-cell RNA sequencing. The successful candidate will join Dr Feng’s group in the Centre for Inflammation Research (CIR), and will link closely with Professor Ponting’s group based at the Institute of Genetics and Molecular Medicine (IGMM) and Dr Campbell’s group in the school of chemistry.

The Feng lab has developed a zebrafish model for in vivo live imaging and genetic analysis of pre-neoplastic cells (PNCs) in its initiating niche in vivo. One of the goals of the lab is to dissect mechanisms that regulate how host cells interact with the initial PNCs in its niche, by fully characterising details of lineage development and the cell-cell interaction network using scRNAseq analysis. The single cell RNAseq data will also be integrated with metabolomic data generated through Imaging Mass Spectrometry (IMS) on intact zebrafish PNC niche.

The ideal candidate will have a strong computational background who is keen to develop their skills and knowledge in the rapidly moving field of single cell transcriptomics, keen to explore and establish novel computational methods for integrated multi-Omic analysis. You will apply and develop computational methods for integrated analysis of single cell transcriptome with metabolomics, to allow discovery and interrogation of cellular subpopulations and cellular functional states during tumour initiation.

Excellent communication skills and a genuine enthusiasm for exploring the interface between computational and experimental biology is essential.

This post is available on a fixed term basis, with a working pattern of 35 hours per week until 31st December 2021.

Informal enquiries to: Yi Feng (yi.feng@ed.ac.uk) or Chris Ponting (chris.ponting@ed.ac.uk)

Reference: 045958

Closing Date: 13th June 2019