Gritstone bio is seeking a Bioinformatics Scientist with significant expertise in computational biology. As part of a team the candidate will build extend and innovate the current platform, to create powerful immunotherapies for cancer patients, and effective vaccines for infectious diseases. The individual will contribute to the development of novel computational and statistical methods and perform analysis of leading proprietary and public genomic datasets.
We are looking for an independent and flexible team player who will thrive in a fast-paced, dynamic, and highly collaborative environment. This is an opportunity to work in an exciting company where bioinformatics analyses drive novel product development.
- Develop and improve statistical and computational methods for high-throughput analysis of large-scale biological data.
- Execute bioinformatics analyses on proprietary and public datasets, including clinical data, to support discovery, pre-clinical and clinical studies, such as identifying novel targets for cancer immunotherapy.
- Refine methodologies for data storage, processing and visualization, and optimize performance and usability.
- Collaborate with various scientific teams including software engineering, mass spectrometry, molecular biology and sequencing, TCR discovery, vaccine technology and translational immunology to design new vaccines, execute experiments and interpret results.
- Mentor junior bioinformatics scientists in computational biology and algorithm strategies.
- Effectively communicate findings to stakeholders
- PhD, MS, or BS in bioinformatics, computational biology, or a related field. Title will be commensurate with experience.
- 4+ years of relevant experience as part of training and/or industrial exposure
- Experience in numerical data analysis and scientific programming, preferably in Python.
- Have hands-on experience with at least one area in Genomics, Proteomics, Immunology, Phylogenetics, Structural Biology and Virology
- Excellent communication and organizational skills. Attention to details.
- Self-motivated and able to work independently as well as collaboratively in a team.
- Expertise with NGS software workflows and analysis of single cell, whole exome, or targeted NGS sequencing data (DNA and RNA).
- Experience in conducting machine learning/statistical experiments and manipulating data sets
- Proficiency with data science and visualization APIs, tools, and frameworks such as Numpy, Pandas, scikit-learn, Keras, TensorFlow and containerization (e.g., Docker)
- Significant experience using TCGA, COSMIC, ENCODE and other key resources relevant for cancer research.
- Demonstrated ability and enthusiasm for working in a multi-disciplinary team including laboratory scientists, data scientists, software engineers, QA and regulatory
- Experience working with cloud computing (AWS), on a Linux based high-performance computing cluster, and contributing to shared code bases