Please review the job summary and apply with a cover letter stating your interest in the position and outline skills and experience that relate to this position along with research interests, career aspiration.

The Kaczorowski lab is seeking a computational biologist who is active at the intersection of single-cell biology and machine learning to join our group in a term-limited position through June 30, 2027. The successful candidate will apply and develop bioinformatics, statistical, machine learning, and/or deep learning approaches to analyze single-cell and spatial data, including single-cell RNA-seq (scRNA-seq), single-nucleus ATAC-seq (snATAC-seq), and 10x single-cell multiome data. The primary responsibilities of the Computational Scientist include deriving biological insight from single-cell sequencing data across neurodegenerative dementias and developing novel methods for computational analysis of emerging technologies, implementing reproducible research practices, providing analysis support for Kaczorowski lab members (both with and without computational experience), and working with our external investigators and consortia (AMP-AD and Resilience-AD) to support knowledge sharing across related projects and help ensure expected milestones are met.

The Kaczorowski lab is in the Department of Neurology at the University of Michigan Medical School located in Ann Arbor, Michigan. The city is ranked among the top 10 places to live in the U.S, with a community that is culturally rich, diverse, pedestrian and bike friendly. The Michigan Neuroscience Institute (MNI) continues to be a leader in innovative, collaborative, and visionary research in the areas of brain science and brain impacting diseases. More information about the Kaczorowski lab can be found at hhttps://kaczorowski.lab.medicine.umich.edu/ or on Twitter @KaczorowskiLab.

The successful candidate will be able to plan, develop, execute, and analyze an independent research project in the context of a supportive lab and institutional environment. In addition, they will supervise and help train graduate students, undergraduate research assistants, and junior technicians in the lab. We are looking for someone that has the aptitude to learn new techniques, works well with others, and possesses strong critical thinking skills. 

• Analyze scRNA-seq, snATAC-seq, multi-omic RNA-/ATAC-seq, and/or spatial transcriptomics data from quality control through generation of actionable results under minimal supervision. 
• Ensure proper documentation and data sharing, including to public repositories (e.g., AD Knowledge Portal). 
• Implement and maintain reproducible research practices 
• Develop and publish manuscripts related to using multi-scale data for predicting disease and biological phenotypes from single-cell sequencing data 
• Attend and present at scientific meetings to maintain and advance technological and scientific expertise. 
• Provide leading contributions to internal and external grant applications. 
• Participate in departmental and project activities, participate in conducting courses and workshops and assist lab members designing for single-nuclei and related experiments and/or analyzing the resulting data.

• Master's degree in bioinformatics, statistics, biostatistics, computer science or a related field or an equivalent combination of education and experience. 
• Proficiency in R and/or Python with experience performing independent analyses of complex datasets.

• Doctoral degree preferred. 
• Excellent organizational and time management, verbal and written communication skills. 
• Previous experience analyzing 10x single-cell, single-nuclei datasets, and/or multiome data. 
• Ability to maintain data storage and familiarity with utilizing Linux-based high performance computing (HPC) resources. 
• Demonstrated ability to integrated into a team setting. 
• An ability to explore and research new technologies and biological domains and meet new challenges creatively and with limited supervision

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

This is a term-limited position through June 30, 2027. The role's deliverables and goals are directly tied to a grant-funded opportunity supported by the National Institutes of Health (NIH). 

At the end of the stated term, your appointment will terminate, and you will not be eligible for Reduction-in-Force (RIF) benefits. This term-limited appointment does not create a contract or guarantee of employment for any period of time as you will remain subject to disciplinary or other performance measures, up to and including termination, at the will of the University in accordance with existing University policy and standards for employee performance and conduct.

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.

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.