BioMarin is the world leader in delivering therapeutics that provide meaningful advances to patients who live with serious and life-threatening genetic diseases. We target diseases that lack effective therapies and affect relatively small numbers of patients, many of whom are children. These conditions are often inherited, difficult to diagnose, progressively debilitating and have few, if any, treatment options. BioMarin will continue to focus on advancing therapies that are the first or best of their kind.
BioMarin's Research and Early Development group is responsible for everything from research and discovery to post-market clinical development. Research and Early Development involves all bench and clinical research and the associated groups that support those endeavors. . Come join our team and make a meaningful impact on patients' lives
The Translational Genomics group within Research and Early Development at BioMarin is at the forefront of prioritizing new disease areas, as well as thinking outside the box when it comes to developing therapeutic approaches. We are seeking a Computational Biologist to join our growing group. We leverage data generated by a wide variety of experiments, from ATAC-seq to CRISPR screens. The ideal candidate will be well-rounded and experienced at processing a wide variety of omics data that will support therapeutic target identification and prioritization efforts. The candidate will identify, integrate, analyze genomics data and effectively communicate results to impact multiple stages of our drug discovery and development pipeline. The successful candidate will have the opportunity to work in a fast-paced and highly collaborative environment. They will be responsible for developing and employing rigorous bioinformatics approaches and for engaging scientists and project teams to leverage genomics data in achieving project objectives.RESPONSIBILITIES
- Apply and develop robust statistical and computational approaches to analyze and integrate omics data to drive disease/target/biomarker identification, mechanistic investigation, causal inference, and hypothesis generation/testing
- Utilize public and internally generated ASE data to identify and prioritize therapeutic targets for drug development.
- Integrate ASE, GWAS, eQTL, and pQTL data towards target identification.
- Evaluate and develop bioinformatics methods to integrate, summarize and report genetic, genomic, and other omics data.
- Work with external collaborators, both academic, and in industry, who are leading experts in the field of computational biology and genetics.
- Serve as a computational biology ambassador on project teams organized around research projects.
- Demonstrated ability to work in cross-functional teams and being an active team contributor.
- Strong scientific curiosity and initiative, knowledge of experimental design
- Proficient in statistical and scripting programming languages such as R, Python, HAIL, etc., and experience with high performance computing or AWS.
- Experience with GTEx, and other public RNAseq datasets. Hands on experience with RNAseq experiment design and the processing of sequencing output.
- Knowledgeable of genomics data processing skillsets such as ATAC-seq, ChIP-seq, HiC and CRISPR screens.
- Familiarity with GATK ASEReadCounter and other ASE focused RNAseq processing pipelines would be a bonus.
- Familiar with, and comfortable interpreting GWAS, eQTL, and pQTL summary statistics.
- A proven track record of publications.
A Ph.D in bioinformatics, biostatistics, computational biology, or quantitative genetics. 2 or more years of industry experience preferred, but not necessary for exceptional candidates.
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, disability status, protected veteran status, or any other characteristic protected by law.