INTERN – RESEARCH AND EARLY DEVELOPMENT - CANCER IMMUNOLOGY, COMPUTATIONAL
Organisation Name: GENENTECH
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The Position Start Date: Summer 2020 Work Hours: 40 hours per week Location: South San Francisco Campus Length of Assignment: 3 months Education Level: PhD Student (pursuing PhD, not completed) Preferred Specialization: Genetics, Bioinformatics, Biostatistics, Data Science (or related field) Department Overview: The mission of the Cancer Immunology group is to bring lasting benefit and cures to cancer patients through innovative scientific discoveries and medicines. By combining clinical observation with laboratory investigation, we will reveal the approaches most likely to work and then build upon our successes to achieve dramatic and long-lasting benefit for patients. Here are some examples of the projects we have for interns this summer… Project #1 Project Description: Work with the Reverse Translation team to build and implement computational pipelines to identify microbiome associations with response in Genentech’s immuno-oncology clinical trials. By utilizing a computational approach, you will analyze large multidimensional datasets from clinical trials and preclinical studies with the goal of identifying variables associated with response to checkpoint inhibitors. Intern Responsibilities: Explore oncology-oriented research utilizing samples & data from human disease cohorts Process and analyze clinical trial samples Data analysis and presentation Intern Qualifications: Working knowledge of at least one programming language (preferably R or python) Experience with bioinformatics, those familiar with analysis techniques for microbiome data sets (16S and/or shotgun metagenomics) will be given precedence Project #2 Project Description: Use statistical analysis of clinical trial data in Cancer Immunology to investigate the role of human immunogenetic variation (HLA, KIR) in outcome and safety phenotypes. The intern will contribute to the human genetics analysis pipeline. Intern Qualifications: Good knowledge of statistics Proficiency in R and linux Good communication skills
