Qiao Liu
Top university
2 weeks ago
Research Assistant in Genomic Foundation Models, Causal Inference, and Regulatory Genomics Yale University in United States
Degree Level
not provided
Field of study
Computer Science
Funding
Full-time research assistant position with close research mentorship, access to Yale’s large-scale GPU computing infrastructure, and opportunities to collaborate across biostatistics, genetics, computational biology, and medicine. No stipend or tuition details are provided.
Country
United States
University
Yale University

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About this position
Research Assistant Opening at Yale Biostatistics
The Liu Lab at Yale University is recruiting a full-time Research Assistant to work onsite at the intersection of genomic foundation models, causal inference, and regulatory genomics. The project focuses on developing trustworthy causal AI methods to understand how genetic variation and molecular regulation contribute to complex phenotypes and disease.
This opportunity is especially well suited for candidates planning to pursue a Ph.D. in AI, statistics, biostatistics, computational biology, or related fields and who want intensive research experience before applying.
Eligibility highlights: applicants should have or soon receive a Bachelor’s or Master’s degree in computer science, statistics, biostatistics, computational biology, or a related field; strong Python and deep learning programming skills are expected; and candidates should be highly motivated to conduct research and publish high-quality work.
What the role offers: close research mentorship, access to Yale’s large-scale GPU computing infrastructure, and collaboration opportunities across biostatistics, genetics, computational biology, and medicine.
How to apply: send a CV to [email protected] and review the full position description at the linked opening page.
Funding details
Full-time research assistant position with close research mentorship, access to Yale’s large-scale GPU computing infrastructure, and opportunities to collaborate across biostatistics, genetics, computational biology, and medicine. No stipend or tuition details are provided.
What's required
Candidates should have or soon receive a Bachelor’s or Master’s degree in computer science, statistics, biostatistics, computational biology, or a related field. Strong Python and deep learning programming skills are required. Applicants should be highly motivated to conduct research and publish high-quality work, and the role is especially suited to future Ph.D. applicants in AI, statistics, biostatistics, computational biology, or related fields.
How to apply
Send your CV to [email protected] and review the full position description at the application link. Use the lab opening page for more details before applying.
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