Research Professional

University of Chicago•Hyde Park, IL

3d•$70,000 - $90,000

About The Position

We bring together faculty and students with diverse perspectives and expertise who are united by a shared passion for understanding genetic variation and drawing out the insights it can provide on gene regulatory mechanisms, evolutionary history, and health outcomes, across developmental stages and environmental contexts. We foster collaborative research that integrates experimental discoveries with statistical modeling and bridges the gap between basic and translational research to ultimately inform strategies for precision medicine. The newly established Chen Lab (https://siwei-lab.org/) is based in the Department of Human Genetics at the University of Chicago. Our research strives to catalyze repeated traversal of the 'genomic medicine cycle,' driving the discovery, biological understanding, and clinical translation of the genetic underpinnings of human disease. Our lab plays a leading role in multiple international consortia, including Epi25, the International League Against Epilepsy (ILAE), and the Genome Aggregation Database (gnomAD). Leveraging advances in genomics technologies, we have made seminal discoveries that elucidate the genetic basis underlying conditions ranging from severe neurodevelopmental disease to population-level phenotypic variation. Our work has been published in high-profile journals including Nature, Nature Genetics, Nature Neuroscience, and others. We are currently expanding efforts to build large-scale data commons for human complex disorders and to integrate emerging technologies such as AI to drive the next wave of genomic and biomedical discovery. We are seeking outstanding researchers to contribute to the development and application of advanced statistical and AI/ML methods for analyzing large-scale genomics data as part of a large NIH-funded international consortium that brings together multiple institutions to analyze genomics data from human cohorts diagnosed with epilepsy.

Requirements

Minimum requirements include a PhD in related field.
Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.

Nice To Haves

Ph.D. in computational biology, bioinformatics, statistics, computer science, AI/ML, or a related quantitative field.
Experience in either: Large-scale genomics data analysis OR Statistical/AI/ML method development applied to biological data.
Proficiency in programming languages and working with high-performance or cloud computing environments.
Practical experience with sequencing or SNP-array data analysis.
Experience with genomics data analysis tools and frameworks (e.g., PLINK, Hail, GATK).
Strong knowledge of modern statistical/AI/ML methodologies in biology.
Solid understanding of genetics principles and genetic association studies.
Demonstrated scientific writing skills in English, evident from first-author journal articles.
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.

Responsibilities

Discuss, plan, and carry out research in a stimulating and collaborative environment.
Develop and apply rigorous methods to investigate associations between genetic and phenotypic variables.
Independently explore, learn, and evaluate state-of-the-art statistical/AI/ML approaches.
Summarize findings in reports, manuscripts, and presentations; publish results in peer-reviewed journals.
Conduct reproducible analyses within an open science framework, including producing open-source pipelines and tools for use by the broader scientific community.
Contribute to the supervision and mentoring of junior researchers.
Collaborate with consortium partners, with excellent opportunities to expand academic networks.
Serves as a resource for collecting data and performing analysis.
Contributes to facilitating and promoting a research project by providing scientific or intellectual information.
Trains new laboratory personnel.
Performs other related work as needed.

Benefits

The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook .

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