University Of Michigan
The Prensner laboratory (https://prensnerlab.org) at Chad Carr Pediatric Brain Tumor Center in the Department of Pediatric Oncology and Department of Biological Chemistry is looking for an exceptional candidate for a unique Applications Programmer / Analyst Associate position focused on computer science, software engineering, and bioinformatics.
This position affords the exciting opportunity to contribute to research with cutting‑edge sequencing‑based data for childhood cancer. Current interests for the lab include big data analyses using ribosome profiling, transcriptome assembly, and proteomics in the context of childhood cancer.
Prior work in the lab has focused on the dark genome in cancer (Prensner et al., Nature Biotechnology 2021), gene discovery in pediatric brain cancer (Hofman et al., Molecular Cell, 2024), and small open reading frames (Prensner et al., Molecular & Cellular Proteomics 2023; Mudge, Ruiz‑Orera, Prensner et al, Nature Biotechnology 2022). We have conducted high‑depth proteomics analyses of cancer and non‑cancer (Deutsch, 2024). We have employed transformer models for small open reading frames in machine learning studies (Clauwaert et al, Nature Communications, 2025).
Who We Are PRENSNER LAB ENVIRONMENT
The Prensner Lab (https://prensnerlab.org) seeks to create a lab culture based on respect, integrity, perseverance, and fun. We aspire to be creative and collaborative scientists who are societally engaged. We regularly collaborate with labs both nationally and globally. We welcome applicants of all kinds.
Benefits What Benefits can you Look Forward to?
Excellent medical, dental and vision coverage effective on your very first day
2:1 Match on retirement savings
Responsibilities* The successful candidate will play a key role in the Prensner laboratory to optimize computational operations within the group. This candidate will have primary responsibility in managing, improving, and developing lab computational resources. Data types are focused on nucleic acid sequencing modalities from in-house assays, public datasets, and external collaborators. The successful candidate will be able to bridge a biological/scientific understanding of the data and the necessary steps to ensure proper computational handling of the data. This includes responsibilities in managing multiple ongoing collaborations, including interpreting data with collaborators. This candidate will receive commensurate academic credit for these efforts.
PRINCIPAL DUTIES AND RESPONSIBILITIES
Data Management:
Organize and handle incoming and outgoing data generated by the lab or handled during collaborations across multiple systems and servers. Lead and manage sequencing data submissions to public data repositories.
System Administration:
Administer and maintain the lab's computational infrastructure, including workstations and servers, by managing software installation, updates, and implementing data backup and recovery strategies.
Pipeline Development:
Design, deploy, and maintain snakemake pipelines for processing biological data in collaboration with lab‑members. This includes managing the need for multiple reference genomes depending on project.
Tool & Database development:
Implement and deploy services to facilitate wet‑lab or dry‑lab tasks, such as queryable databases or web applications, to streamline data access and facilitate research.
Documentation:
Create documentation on services, pipelines and protocols within the lab to facilitate onboarding and continuity.
Other tasks as required
Required Qualifications* Education
Bachelor degree in computational biology, bioinformatics, the life sciences, engineering, or a related discipline.
Skills and abilities
1‑2 years systems analysis/programming activities
Fluency with R, Python and/or Bash.
Prior experience with writing code in a variety of project settings
Exceptional organization and attention to detail are essential
Excellent communication skills and the ability to interact with all levels of staff and with external contacts are needed
Ability and eagerness to learn in a self‑motivation environment.
Desired Qualifications* Education
Master's degree in computational biology, bioinformatics, the life sciences, engineering, or a related discipline.
Skills and abilities
Unix/Linux experience is also helpful
Prior experience with nucleotide sequencing data is highly desired
Familiarity with Docker containers and/or Snakemake workflows is helpful
Modes of Work 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.
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.
Application Deadline 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.
U‑M EEO Statement The University of Michigan is an equal employment opportunity employer.
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This position affords the exciting opportunity to contribute to research with cutting‑edge sequencing‑based data for childhood cancer. Current interests for the lab include big data analyses using ribosome profiling, transcriptome assembly, and proteomics in the context of childhood cancer.
Prior work in the lab has focused on the dark genome in cancer (Prensner et al., Nature Biotechnology 2021), gene discovery in pediatric brain cancer (Hofman et al., Molecular Cell, 2024), and small open reading frames (Prensner et al., Molecular & Cellular Proteomics 2023; Mudge, Ruiz‑Orera, Prensner et al, Nature Biotechnology 2022). We have conducted high‑depth proteomics analyses of cancer and non‑cancer (Deutsch, 2024). We have employed transformer models for small open reading frames in machine learning studies (Clauwaert et al, Nature Communications, 2025).
Who We Are PRENSNER LAB ENVIRONMENT
The Prensner Lab (https://prensnerlab.org) seeks to create a lab culture based on respect, integrity, perseverance, and fun. We aspire to be creative and collaborative scientists who are societally engaged. We regularly collaborate with labs both nationally and globally. We welcome applicants of all kinds.
Benefits What Benefits can you Look Forward to?
Excellent medical, dental and vision coverage effective on your very first day
2:1 Match on retirement savings
Responsibilities* The successful candidate will play a key role in the Prensner laboratory to optimize computational operations within the group. This candidate will have primary responsibility in managing, improving, and developing lab computational resources. Data types are focused on nucleic acid sequencing modalities from in-house assays, public datasets, and external collaborators. The successful candidate will be able to bridge a biological/scientific understanding of the data and the necessary steps to ensure proper computational handling of the data. This includes responsibilities in managing multiple ongoing collaborations, including interpreting data with collaborators. This candidate will receive commensurate academic credit for these efforts.
PRINCIPAL DUTIES AND RESPONSIBILITIES
Data Management:
Organize and handle incoming and outgoing data generated by the lab or handled during collaborations across multiple systems and servers. Lead and manage sequencing data submissions to public data repositories.
System Administration:
Administer and maintain the lab's computational infrastructure, including workstations and servers, by managing software installation, updates, and implementing data backup and recovery strategies.
Pipeline Development:
Design, deploy, and maintain snakemake pipelines for processing biological data in collaboration with lab‑members. This includes managing the need for multiple reference genomes depending on project.
Tool & Database development:
Implement and deploy services to facilitate wet‑lab or dry‑lab tasks, such as queryable databases or web applications, to streamline data access and facilitate research.
Documentation:
Create documentation on services, pipelines and protocols within the lab to facilitate onboarding and continuity.
Other tasks as required
Required Qualifications* Education
Bachelor degree in computational biology, bioinformatics, the life sciences, engineering, or a related discipline.
Skills and abilities
1‑2 years systems analysis/programming activities
Fluency with R, Python and/or Bash.
Prior experience with writing code in a variety of project settings
Exceptional organization and attention to detail are essential
Excellent communication skills and the ability to interact with all levels of staff and with external contacts are needed
Ability and eagerness to learn in a self‑motivation environment.
Desired Qualifications* Education
Master's degree in computational biology, bioinformatics, the life sciences, engineering, or a related discipline.
Skills and abilities
Unix/Linux experience is also helpful
Prior experience with nucleotide sequencing data is highly desired
Familiarity with Docker containers and/or Snakemake workflows is helpful
Modes of Work 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.
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.
Application Deadline 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.
U‑M EEO Statement The University of Michigan is an equal employment opportunity employer.
#J-18808-Ljbffr