À propos
A healthier future. It's what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That's what makes us Genentech, a member of the Roche Group! The department of Translational Safety is looking for a computational toxicology data scientist to provide scientific leadership and contribute to the comprehensive and integrated safety profiling of Genentech drug candidates. The successful candidate will work closely with stakeholders across the company to analyze diverse data and develop novel computational tools that support safety-related decisions. The Role: In-depth analyses of multifactorial data streams from new and established toxicity assays to support decision on preclinical candidate safety Integration of large scale omic data sets in support of in vitro assay development, NAM validation, and project-specific investigations into toxicity mechanisms Curation of diverse historical data to develop predictive AI/ML models aimed at profiling drug candidates throughout the Genentech pipeline Identification, evaluation, and proposal of novel computational approaches to augment safety predictions and impact safety-related decisions throughout the drug-development pipeline Collection and curation of clinical and preclinical in vivo data to support translational validation of NAMs Work with cross-functional teams including toxicologists, biologists, chemists, data & computer scientists to develop fit-purpose computational tools and drive the adoption of in silico NAMs throughout the drug development pipeline Actively engage with academic groups at the forefront of AI/ML, toxicology, and informatics Publish high quality impactful scientific articles and present at conferences, business meetings, and academic institutions Who You Are: Education: PhD in computational biology, computational toxicology, computational chemistry, biomedical data science, statistics, machine learning, biotechnology, or a related field with 0-5 years of experience Omics Expertise: In-depth understanding of modern omics data and analytical pipelines, with an emphasis on single-cell and spatial transcriptomics Toxicology Background: Scientific background in toxicology or closely related life science, with a proven record of curating and interpreting bioassay data Safety & Screening: Preferred experience with safety screening pipelines, drug candidate de-risking, and a general understanding of 3D in vitro systems Machine Learning: Clear understanding of contemporary ML concepts and demonstrated interest in applying them to life sciences problems Programming Skills: Strong programming skills in R or Python for large-scale data management and machine learning Data Infrastructure: Experience with cloud computing, database architecture, and SQL Data Analysis: Practical understanding of data processing and statistics in biological sciences and a record of integrating data across sources Advanced ML Experience (Preferred): Experience with image processing, pattern recognition, automated literature data extraction, and/or developing LLMs, knowledge graphs, or generative models Communication & Leadership: Ability to communicate and collaborate across life and computational sciences, with a demonstrated track record of technical leadership and scientific contributions Relocation benefits are available for this job posting. The expected salary range for this position based on the primary location of South San Francisco, CA is $156,200 to $290,200. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below. Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
Compétences linguistiques
- English
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