The Chen Lab at the University of Chicago is seeking to advance large-scale genomic studies by analyzing genetic association data, performing multi-omics analysis, developing statistical and AI/ML methods, and building software platforms to understand the genetic basis of human diseases and translate discoveries into novel therapeutic strategies.
Requirements
- Proficiency in programming languages and working with high-performance or cloud computing environments.
- Practical experience in either large-scale genomics data analysis or statistical/AI/ML method application to biological data.
- Familiarity with omics datasets and modern statistical/AI/ML methodologies in biology.
- Basic knowledge of genetics principles.
Responsibilities
- Processes and analyzes large-scale genomics datasets for disease association studies.
- Develops and/or applies statistical and AI/ML models for biologically informed gene discovery and variant interpretation.
- Builds and implements computational workflows for data quality control, annotation, and downstream analyses.
- Summarizes findings in reports, manuscripts, and presentations for internal and external dissemination.
- Maintains well-documented, reproducible code and workflows.
- Assists in analyzing data for the purpose of extracting applicable information.
- Maintains and analyzes statistical models using general knowledge of best practices in machine learning and statistical inference.
Other
- Discusses, plans, and carries out research in a stimulating and collaborative environment.
- Strong organizational skills, attention to detail, and work independently and in a team setting.
- Proactive mindset with strong communication skills to work effectively in an interdisciplinary team.
- Enthusiasm for initiating innovative secondary analyses, such as integration with multimodal functional and clinical data from external resources.
- Minimum requirements include a college or university degree in related field.
