Scientist, Computational Biology

Denali Therapeutics is dedicated to developing breakthrough therapies for neurodegenerative diseases through our deep commitment to degeneration biology and principles of translational medicine.

We are looking for a Computational Biologist to join our Discovery Genomics team to study the biology underlying neurodegeneration in vitro (e.g. in iPSC-derived CNS cell types) and in vivo.

Please apply on Denali's website

You will join a group that values diversity of thought, continuous learning, and explores impactful ways of applying computational approaches to target and biomarker discovery. You are a strong communicator and will become a valued collaborator on cross-functional teams featuring e.g. Biologists, Chemists, Biomarker Scientists, Protein Engineers, and Data Scientists.

The successful candidate has broad expertise in the analysis of genome-scale data - e.g. bulk and single-cell transcriptomics, proteomics or metabolomics, etc - and will use this knowledge to deeply characterize cellular state and responses to therapeutic interventions in vitro and in vivo.

Responsibilities

• Thoughtful design and reproducible analysis of genome-scale experiments, e.g. single-cell / single-nuclei, bulk, and spatial transcriptomics data, and distilling key takeaways.
• Identifying and applying best practices to data collection, analysis & sharing, making datasets findable, accessible, interoperable and reusable (FAIR).
• Communicating your findings to specialists and non-specialists on cross-functional teams, and the broader research community through presentations and publications.

Requirements

• Driven by the desire to make a positive impact on human health through rigorous collaborative science.
• A PhD in a relevant field, including — but not limited to — Computational Biology, Bioinformatics, Genomics, Biostatistics, etc, with or without post-doctoral or industry experience. Previous work in the field of neurodegeneration is a plus.
• Proven track record of analyzing high throughput data as evidenced by high quality publications and/or conference talks in this area.
• Extensive experience with a high-level data analysis language like R or Python.
• Understanding of statistical approaches to the analysis of high-dimensional data.
• Knowledge of the Bioconductor software ecosystem and version control (e.g. GitHub) is a plus.
• Experience with a workflow orchestrator like Nextflow, Snakemake, etc is a plus.