Title: Bioinformatics/AI Scientist Oncology
Duration: 6 months
Location: South San Francisco, CA

The Oncology and BRAID teams in the Computational Biology and Translation Pillar of gRED Computational Sciences (gCS) are seeking a talented and highly motivated Computational Scientist (Contract) with a strong analytical background in Bioinformatics and ML/AI.
The successful candidate will have a proven track record in multi-omics analysis and the application of deep learning and transformer models to biomedical and clinical data.
Position Details
This will be a short-term, full-time contract position until December 19, 2025.
This position can be on-site in South San Francisco, CA, or remote (US or Canada only) during normal Pacific timezone business hours.

Responsibilities
● Work under the supervision of group leaders in Computational Biology and Translation to benchmark ML/AI models integrating large-scale multiomics preclinical and clinical datasets.
● Write scalable Python code to benchmark the performance of state-of-the-art ML models on predefined preclinical and clinical tasks.
● Produce reports on the performance of different ML methods and present results.
● Suggest new directions for benchmarking and improvement to predictive models.
● Document code, analysis, and findings, including standardization of analytical workflows.

Requirements
● PhD in Computer Science, Computational Biology, Bioinformatics, or a related field.
● Extensive experience (6+ years) in large-scale bulk data analysis (RNA, WES), including gold-standard methods and Client, advanced analytical techniques.
● Experience (3+ years) in training and applying modern ML architectures and models to omics data.
● Expertise in cancer biology or clinical omics data.
● Proficiency in Python, shell scripting.
● Experience working with Git and high-performance computing.
● High self-motivation and commitment to delivering high-quality results.
● Ability to produce rigorous analysis with minimal supervision, including meeting key deadlines and making sensible independent decisions.
● Excellent communication skills and experience working as part of a team.
● Curiosity and desire to learn more about applications of AI methods to pharmaceutical research.