Bioinformatics/AI Scientist - Oncology
Apply NowCompany: HonorVet Technologies
Location: South San Francisco, CA 94080
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.