Posted 2 days ago
Description
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.
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.
