【简介】博士后招聘网整理分享“德国Biberach/Riss计算生物学博士后职位招聘”，浏览查询更多博士后招聘计划请访问博士后招聘网。

As part of our new research strategy we are seeking for a computational biologist to support a research project on studying molecular mechanisms driving COPD in partnership with Imperial College London (ICL). The department of Immunology and Respiratory Research (I&R) offers a position for highly qualified and strongly motivated postdoctoral fellow at our research site in Biberach, Germany.

The position is limited to 2 years.

Note: To make it easy to find our job postings we use the customary title “post doc”. Of course, this posting is not only addressed to applicants directly after completing their doctorate but to all qualified candidates.

Tasks & responsibilities

-With your expertise in computational biology, you contribute input to experimental design, quality control, basic and downstream analysis of single cell RNA-Seq data.

-You generate results from computational biology analysis such as single cell RNA-Seq related algorithms, pathway analysis, biomarker analyses, gene prioritization, etc.

-Moreover, you keep track of relevant literature and integrate publicly available relevant datasets that can enhance the interpretation of the results.

-Participating in the publication of results in peer-reviewed journals and at scientific congresses is also your task.

-You are also responsible for interfacing with collaborators in the ICL and BI experimental groups as well as the ICL and BI computational biology groups.

Requirements

-PhD degree or equivalent qualification in Bioinformatics, Computational Biology, Computer Science, Biostatistics or related fields

Outstanding knowledge and a broad spectrum in bioinformatics and computational biology, analysis of RNA-Seq and other high-throughput data

-Several years of experience in R/Bioconductor or Python

-Skills to turn large datasets into relevant insight in concrete biological and disease related topics in interdisciplinary collaborations

-Experience in analyzing data derived from immunology relevant cells is appreciated

-Ideally previous working experience with scRNA-Seq data; Experience with machine learning and network / systems biology approaches is a plus

-Focused working style, flexibility as well as innovative thinking, problem solving and analytical skills

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