At eGenesis, we aspire to deliver safe and effective human transplantable cells, tissue and organs utilizing the latest advancements in genome editing.
We are seeking a computational biologist experienced in transcriptomics, single-cell sequencing, and/or epigenomics to join our team. In this position, you will support our goals by employing innovative sequencing technologies and machine learning techniques to tackle outstanding questions in xenotransplantation.
You will be involved in ongoing exploratory and preclinical studies in all aspects including project design, pipeline development, data analysis, and presentation of results. Your work, in collaboration with cross-functional teams, will inform decision making critical to our path forward, and to advance the field through publications and conference attendance. You will leverage your track record of positive intellectual and practical contributions to projects and teams through publications or comparable prior experiences. Furthermore, you will have demonstrated strong foundations in statistics, machine learning, computer science, programming, and/or algorithms. Knowledge of molecular biology, gene editing, and/or immunology is a plus.
- Process, analyze, and present novel and exciting next generation sequencing data for large exploratory and preclinical studies, with a focus on transcriptomics and functional genomics
- Collaborate with a diverse team of scientists to plan analysis and experiments to improve product performance and answer critical outstanding questions in xenotransplantation
- Utilize state-of-the-art machine learning, statistics, and multi-omics methods to understand the gene and protein networks driving important biological processes, and providing actionable recommendations from these findings
- Become a scientific leader by keeping up to date with the latest literature, attending conferences, and supporting publication of key results
- A Ph.D., OR a master's degree with 3+ years of experience in bioinformatics, computational biology, engineering, computer science, or a related quantitative field
- A strong ability to program with R/bioconductor is required, and Python a plus
- Experience analyzing transcriptomics, single-cell sequencing, and/or epigenomics is preferred, including commonly associated software
- Knowledge of molecular biology, gene editing, and/or immunology is a plus
- Knowledge of omics, multiomics, and other high-dimensional data analysis
- Strong foundations in statistics and machine learning
- Experience with HPCs or cloud computing in e.g., AWS or GCP
- Familiarity with standard bioinformatics pipeline development such as NextFlow or Snakemake
- Exceptional communication skills and ability to collaborate with diverse team members
- A record of independence and an ability to troubleshoot complex technical problems
- A propensity to keep up with the literature and best practices in the field