Exciting opportunity for a Computational Biologist at Denali Therapeutics in South San Francisco, CA, USA:
Do you enjoy analyzing and integrating high-dimensional human data? Then help us identify & validate biomarkers to defeat neurodegeneration!
Recent breakthroughs in identifying the genetic causes underlying neurodegenerative diseases offer an opportunity for the discovery and development of effective treatments for Alzheimer’s disease, Parkinson’s disease, Amyotrophic Lateral Sclerosis (ALS) and other neurodegenerative diseases.
To translate these genetic insights into actionable drug targets and novel biomarkers, we are seeking a Computational Biologist to join Denali at our headquarters in South San Francisco, California.
A successful candidate will analyze and integrate data from multiple domains (including Genetics, Transcriptomics, Metabolomics, Proteomics at the tissue and single-cell levels), and employ rigorous computational methods to prioritize and validate biomarkers of disease progression, target engagement, pathway modulation and for deep patient phenotyping.<h3>Responsibilities</h3>
You will contribute to defeating neurodegeneration by
- Becoming the subject matter expert on large internal and external multi-omics datasets from human cohorts and in vivo models of neurodegeneration.
- Defining multivariate predictors of disease status, progression and treatment response.
- Leveraging observational data for biomarker discovery & validation, including rigorous quality assessment and critical assessment of potential confounders.
- Designing data analysis strategies, implementing them using reproducible workflows, and interpreting the results.
- Collaborating with Scientists from diverse fields, e.g. Translational Sciences, Genomics, Biology, Statistics, Toxicology and Clinical Sciences.
- Communicating your findings to specialists and non-specialists on cross-functional teams, and the broader research community through presentations and publications.
- Identifying opportunities for public-private partnerships, e.g. by representing Denali within consortia that generate data on large human cohorts.
- Driven by the desire to make a positive impact on human health through rigorous collaborative science.
- PhD in a relevant field, e.g. Computational Biology, Epidemiology, Neuroscience, Statistics or similar. Postdoctoral experience is a plus.
- Proven track record of analyzing and integrating high-dimensional human phenotypes, e.g. gene expression, proteomics, mass spectrometry or genetics data.
- Deep understanding of statistical approaches to the analysis of high-dimensional data, e.g. identification of patient subgroups and robust biomarker signatures. Experience in the field of neurodegeneration is a plus.
- Experience accessing and managing public human datasets, e.g. PPMI, ADNI, UK Biobank or similar, is a plus.
- Extensive experience with R, Python or other languages commonly used for large-scale data analysis. Experience with the Bioconductor software ecosystem and version control (e.g. github) is a plus.
- Highly independent, curious and creative with excellent time-management skills; embraces a "continuous improvement" culture.