SCIENCE-JOBS-DE

Analysis and visualization of complex multi-phenotype data from high-throughput image-based RNAi screening experiments (Heidelberg)

Image-based high-throughput RNAi screening experiments produce complex phenotypes with multiple features being assessed in a single image. The extent and complexity of these data pose a big challenge with respect to data management and interpretation. The aim of the project, which is part of a new national bioinformatics initiative (de.NBI), is to develop novel analysis methods for the interpretation and comparison of multi-phenotype data as well as functionalities for their integration and visualization. These functionalities shall be integrated into the GenomeRNAi database (www.genomernai.org) to provide a user-friendly presentation, and interactive analysis tools of image-based multi-phenotype data. Furthermore, the candidate should contribute to the development of concepts for the integration of multi-phenotype data with other “omics” data from external resources.

We are looking for a highly motivated PhD student with a background in bioinformatics or computational biology. The successful candidate will have strong skills in image analysis, statistics and R/Bioconductor programming. Experience with JAVA web application development, Javascript visualization frameworks (e.g. d3.js) and web services (e.g. REST, SOAP) will be advantageous.

More information and application via the HBIGS graduate programme:
http://tinyurl.com/owzpzts


Esther Schmidt
e.schmidt@dkfz.de
German Cancer Research Center (DKFZ)
Heidelberg