The Athey Lab with Gilbert S. Omenn Department of Computational Medicine and Bioinformatics is seeking a highly skilled and experienced Senior-Level Bioinformatician to exclusively manage coding, data processing, and analytical responsibilities associated with Projects 1a-1c. The successful candidate will leverage advanced computational methods, including Large Language Models (LLMs), and manage substantial datasets derived from Electronic Health Records (EHRs) and large-scale genomic databases. The role demands expertise in creating and optimizing computational pipelines, performing retrospective clinical analyses, and generating statistically robust insights through sophisticated causal inference methodologies.
- Develop, deploy, and optimize computational pipelines and custom scripts using Python and Bash scripting.
- Apply and manage advanced computational methods involving Large Language Models (LLMs) for processing and analyzing extensive EHR datasets.
- Efficiently handle large-scale genomic data acquired from sources such as the Michigan Genomics Initiative (MGI).
- Conduct retrospective clinical study designs, implement statistical analyses, and derive meaningful conclusions through causal inference and modeling.
- Organize, curate, and manage large-scale bioinformatics and clinical datasets, ensuring data integrity, quality control, and reproducibility of results.
- Collaborate closely with interdisciplinary research teams to translate complex data analyses into actionable insights.
Bachelor degree in recognized field of science or learning which is directly related to the position.
- Advanced proficiency in Python and Bash scripting, including development and maintenance of automated computational workflows.
- Expertise in Large Language Models (LLMs) for biomedical data analysis.
- Demonstrate experience managing and analyzing large-scale Electronic Health Record (EHR) datasets.
- Proven ability to execute retrospective clinical studies including the design and implementation of statistical tests and causal inference modeling.
- Extensive experience working with high-performance computing clusters, parallel processing, and data pipelining.
- Strong analytical and statistical background, with the capability to interpret complex biomedical data accurately.
- Direct experience handling and interpreting large-scale genomics datasets.
- Familiarity with Single Nucleotide Polymorphism (SNP) genotyping arrays, imputation techniques, and SNP panel data.
- Experience with pharmacometabolomic data interpretation, particularly in translational or clinical contexts.
Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.
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Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.
The University of Michigan is an equal employment opportunity employer.
