Requirements
- You have a PhD plus Postdoctoral training or equivalent industry experience in bioinformatics, biostatistics, computational biology or similar. Or you might have a PhD plus Postdoctoral training in molecular biology, oncology, etc. combined with a very strong record of high- throughput data analysis, supported by publications in this area.
- You have experience in analyzing a diverse set of genomics datasets, preferably those related to mechanisms of gene regulation, such as ChIP-Seq or ATAC-Seq, and single cell approaches.
- You are comfortable writing code in languages such as R (preferred), Python or Perl for complex data analysis.
- You are able to present complex results, both verbally and in writing, to both bioinformatics and non-bioinformatics audiences.
- You are able to work both independently and collaboratively, and to handle several concurrent, fast-paced projects.
- You have a strong interest in contributing to biomedical discoveries and scientific efforts, including the study of inflammation and cell death pathways, and you are eager to learn.
- You have an understanding of the statistical principles behind current best practices in high-throughput molecular data analysis and enjoy adapting existing algorithms – or develop new ones – to enable analysis of data from novel, cutting-edge assays.
