Full-Time Research Assistant

Statistics Interest Group; New Haven, Northern (CT, KY); Hybrid; USD 39,000 - 52,000; Full time

Job summary

Yale University, in New Haven, seeks a Full-Time Research Assistant in the Liu Lab, Biostatistics. You will work with Dr.

Qiao Liu on projects at the intersection of generative AI, causal inference, and regulatory genomics, handling genomic data preprocessing and analysis. Responsibilities include implementing ML methods, running experiments on Yale HPC/GPU systems, and maintaining clear, reproducible code and documentation.

Qualifications

• Bachelor's or master's degree in computer science, statistics, biostatistics, computational biology, bioinformatics, data science, or a related field.
• Strong Python programming skills are expected.
• Experience with PyTorch or TensorFlow and Linux/HPC environments is preferred.
• Research experience in machine learning, generative modeling, causal inference, or computational genomics is an advantage.

Responsibilities

• Preprocess and analyze genomic and biomedical datasets.
• Implement and evaluate machine-learning and statistical methods.
• Run computational experiments on Yale HPC/GPU systems.
• Maintain clear, reproducible code and documentation.
• Summarize relevant literature and results; contribute to figures, presentations, and manuscripts.

Skills

Python

PyTorch/TensorFlow

Linux HPC

Education

Bachelor's degree

Master's degree

Job description

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Yale University – Full-Time Research Assistant

Company Name Yale University

Position Title Full-Time Research Assistant

Company Information

The Liu Lab in the Department of Biostatistics at Yale University develops statistically principled, AI-powered methods for large and complex biomedical data. Our work connects genetic variation, molecular regulation, perturbation response, and disease phenotypes to advance mechanistic understanding and causal discovery. The lab offers a collaborative environment spanning AI, statistics, genomics, and public health, with access to Yale's large-scale GPU computing resources.

Duties and Responsibilities

Work closely with Dr. Qiao Liu and interdisciplinary collaborators on projects at the intersection of generative AI, causal inference, and regulatory genomics. Responsibilities include preprocessing and analyzing genomic and biomedical datasets; implementing and evaluating machine-learning and statistical methods; running computational experiments on Yale HPC/GPU systems; maintaining clear, reproducible code and documentation; summarizing relevant literature and results; and contributing to figures, presentations, and manuscripts. The RA will receive mentorship and opportunities to develop skills in AI, causal inference, and computational genomics.

Position Qualifications

Bachelor's or master's degree in computer science, statistics, biostatistics, computational biology, bioinformatics, data science, or a related field. Strong Python programming skills are expected. Experience with PyTorch or TensorFlow and Linux/HPC environments is preferred. Research experience in machine learning, generative modeling, causal inference, or computational genomics is an advantage. We value intellectual curiosity, careful and independent work, strong communication and teamwork, and enthusiasm for interdisciplinary biomedical research.

Salary Range 45,600 per year

See benefit from Yale official website: https://postdocs.yale.edu/postgrads/being-a-postgrad-at-yale/postgraduate-compensation

We prefer an RA candiate, who is expected to join Liu lab very soon.