Position Location: Menlo Park, California
We are seeking a highly motivated individual to support NGS pipeline development and data analysis for clinical studies, translational and pre-clinical research. The successful candidate will apply advanced bioinformatics and statistical skills to develop and maintain NGS pipelines, process high-dimensional genomic data, and build statistical & machine learning models for NGS data derived from clinical development programs and translational research.
- Drive the design, the development, and the maintainence of end-to-end bioinformatics pipelines to work with multi-omics sequencing data from FFPE tissue to liquid biopsy samples
- Lead the development of novel statistical and machine-learning based methods to optimize detection of mutations, copy number alterations, genomic rearrangements, HLA, and oncovirus.
- Lead and perform benchmarking for testing pipeline accuracy and performance.
- Interact with key internal stakeholder and external investigators for data processing, analysis, and interpretation.
- Collaborate with translational bioinformatics scientist to facilitate biomarker analyses of NGS data from clinical trials and translational research.
Skills and qualifications:
- Experience in managing cross functional team members during trial execution a must.
- Strong knowledge of ICH/GCP guidelines with working knowledge of GLP/GCLP preferred.
- Ability to function in a fast paced, dynamic environment.
- Ability to independently develop and deploy action plans to meet company needs.
- Strong interpersonal and negotiation skills.
- Proven complex problem solving and decision-making skills.
- Must be a demonstrated self-starter and team player with strong interpersonal skills
- Excellent written and verbal skills.
- PhD in Bioinformatics, or Computational Biology, Computer Science, Biostatistics or related field or equivalent work experience
- 2+ years of experience in working with whole genome sequencing, whole exome sequencing, bisulfite sequencing, and whole transcriptome sequencing data
- Experience with standard bioinformatics algorithm and tools, such as BWA, GATK
- Experience with statistical and machine learning techniques, such as linear regression, random forest, bayes inference, etc.
- Proficiency in Python, R, and Linux shell scripting language