A 2-year fulltime position is funded by an Industrial-Academic research collaboration with Novo Nordisk, Denmark and can be started as soon as possible.
This project aims to harness the power of multi-modal cutting-edge single cell technologies using state-of-the-art statistical and machine learning tools to study kidney and cardiovascular diseases, improve our disease understanding, and eventually lead to target discovery for cell-based interceptive medicine.
Come join the amazing and dynamic team of researchers to get the best out of industry (Novo Nordisk) and academia (RWTH Aachen University), lead kidney and cardiovascular systematic data-driven target discovery efforts, and contribute to clinically actionable targets.
Join the Hayat Lab in Translational Data Science in collaboration with the Kramann Lab, and Bioinformatics and Data Mining department at Novo Nordisk.
The application deadline for the advertised position GB-P-34060 is 31th of March 2022.
Task:
- The candidate will lead a project of multi-modal single-cell research including single cell/ nuclear RNA-seq, snATAC-seq data integration
- Work on personal project and contribute to ongoing projects in the lab aimed to gain new insights in understanding disease mechanisms with a major focus on kidney and cardiovascular disease
- Develop tools for systematic data-driven discovery of new therapeutic targets and biomarkers
- The position will involve regular interaction, mentoring, brain-storming, meetings and a short-term stay at Novo Nordisk, Copenhagen, Denmark
- The position provides a unique opportunity to experience both industrial and academic research
The University provides a highly collaborative and international research environment
Your Profile:
- PhD in a quantitative discipline, e.g. Bioinformatics, computer/ data science
- Experience with sc/ snRNAseq data integration and a basic understanding of biology is preferred
- Experience with transcriptomic data analysis
- Fluent English skills (Level C1)
- Excellent teamwork skills
- Good knowledge in programming with Python/ R
- Good knowledge of computational tools (Scanpy/ Seurat), basic regression and classification analysis
- Familiarity with advanced statistical and machine learning is preferred
Interested candidates kindly follow the link in the post for more details.
