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Postdoc Single Cell Rna Sequencing Analysis Jobs in Michigan

Contribute to gene expression profiling studies (qPCR, bulk and single-cell RNA-seq) of sorted ... Analyze, interpret, and present data at lab meetings and scientific conferences; contribute to ...

... sequencing, sample prep/ library prep for genomic analysis, PCR, qPCR and digital PCR. * Experience selling technologies for single cell sequencing, transcriptomics or proteogenomics highly desired.

The postdoctoral research associate will be involved in several projects focusing on bioinformatics analyses of whole genome sequencing, RNA sequencing, and metagenomic/metatranscriptomic datasets ...

We combine statistical genetics, single-cell and single-nucleus multi-omics, and computational ... The position has scientific latitude: we expect the postdoc to drive analytical strategy, make and ...

We combine statistical genetics, single-cell and single-nucleus multi-omics, and computational ... The position has scientific latitude: we expect the postdoc to drive analytical strategy, make and ...

We combine statistical genetics, single-cell and single-nucleus multi-omics, and computational ... The position has scientific latitude: we expect the postdoc to drive analytical strategy, make and ...

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Postdoc Single Cell Rna Sequencing Analysis information

What does a postdoc in single cell RNA sequencing analysis do?

A Postdoc in Single Cell RNA Sequencing (scRNA-seq) Analysis specializes in analyzing gene expression data from individual cells. Their main responsibilities include processing raw sequencing data, performing quality control, identifying cell types or states, and interpreting biological insights from the data. They often develop or apply computational methods to handle large datasets, collaborate with experimental biologists, and present findings through publications or conferences. The ultimate goal is to understand cellular heterogeneity and uncover new biological mechanisms at the single-cell level.

What are the key skills and qualifications needed to thrive as a postdoc in single cell RNA sequencing analysis, and why are they important?

To thrive as a Postdoc in Single Cell RNA Sequencing Analysis, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by a PhD in a relevant field. Proficiency with computational tools such as R, Python, and specialized single-cell analysis platforms (e.g., Seurat, Scanpy), as well as experience with data visualization and next-generation sequencing, is essential. Strong problem-solving abilities, effective communication, and collaboration skills help distinguish top candidates in interdisciplinary research environments. These skills enable accurate data interpretation, drive innovation, and support impactful scientific discoveries in complex biological systems.

What are some common challenges faced by postdocs working in single cell RNA sequencing analysis, and how can they be addressed?

Postdocs in single cell RNA sequencing analysis often encounter challenges such as managing large and complex datasets, integrating multi-omic data, and staying current with rapidly evolving bioinformatics tools. Collaborating closely with wet lab scientists and computational biologists is essential to interpret results accurately and to troubleshoot technical issues. Building strong programming and statistical skills, as well as actively participating in lab meetings and seminars, can help address these challenges and contribute to both personal growth and successful project outcomes.

What is the difference between Postdoc Single Cell Rna Sequencing Analysis vs Postdoc Bioinformatics?

AspectPostdoc Single Cell Rna Sequencing AnalysisPostdoc Bioinformatics
Required CredentialsPhD in Biology, Genetics, or related field; experience in sequencing data analysisPhD in Computer Science, Bioinformatics, or related field; programming skills essential
Work EnvironmentResearch labs focusing on genomics and cell biologyResearch institutions, biotech companies, or academic labs with computational focus
Employer & Industry UsageBiotech, academic research, pharmaceutical companiesBiotech, healthcare, academic research, industry R&D

Postdoc Single Cell Rna Sequencing Analysis specialists focus on analyzing single-cell transcriptomics data, often requiring biological expertise and lab experience. In contrast, Postdoc Bioinformatics roles emphasize computational skills and software development to interpret large datasets across various biological contexts. Both roles are vital in genomics research but differ in their primary focus and skill set.

What are popular job titles related to Postdoc Single Cell Rna Sequencing Analysis jobs in Michigan?

For Postdoc Single Cell Rna Sequencing Analysis jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Postdoc Single Cell Rna Sequencing Analysis jobs in Michigan look for?

The top searched job categories for Postdoc Single Cell Rna Sequencing Analysis jobs in Michigan are:

What cities in Michigan are hiring for Postdoc Single Cell Rna Sequencing Analysis jobs?

Cities in Michigan with the most Postdoc Single Cell Rna Sequencing Analysis job openings:

Infographic showing various Postdoc Single Cell Rna Sequencing Analysis job openings in Michigan as of August 2026, with employment types broken down into 71% Full Time, and 29% Contract. Highlights an 100% In-person job distribution.

Bioinformatics Scientist / Computational Biologist

University of Michigan

Ann Arbor, MI • On-site

$88K - $109K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

This job post has expired 1 day ago. Applications are no longer accepted.


University Of Michigan rating

8.0

Company rating: 8.0 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

190th of 627 rated colleges and universities


Job description

How to Apply
A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.
Who We Are
The Center for Statistical Genetics designs and carries out some of the world's largest human genetic studies, integrating genomic, molecular, clinical, and epidemiologic data from hundreds of thousands of participants. Our investigators develop statistical methods, computational tools, and analytical approaches that enable discoveries in human health and disease and support researchers worldwide.
Job Summary
The Center for Statistical Genetics (CSG) in the Department of Biostatistics at the University of Michigan seeks a highly motivated Bioinformatics Scientist to join a collaborative team supporting large-scale genomic research within the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and related studies.
You will contribute to the analysis of large-scale whole-genome sequencing datasets, including both short-read and long-read sequencing technologies, and will play a key role in the development and application of computational approaches for single-cell and bulk omics studies. This position offers you the opportunity to work with one of the world's largest collections of human genomic and phenotypic data while collaborating with investigators across genetics, genomics, epidemiology, biostatistics, and computational biology.
We are especially interested in candidates with demonstrated expertise in single-cell RNA-seq analysis and/or whole-genome sequencing analysis. Individuals who have led genomic analyses resulting in publications, developed reusable computational workflows, or worked with large-scale consortium datasets such as TOPMed, All of Us, UK Biobank, or similar resources are strongly encouraged to apply.
We recognize that excellent candidates may bring different combinations of skills and experiences. While no applicant is expected to possess expertise in all areas, experience in one or more of the following domains would be particularly valuable: single-cell transcriptomics, long-read sequencing, large-scale whole-genome sequencing analysis, cloud-based genomics, workflow development, and multi-omics data integration.
The position may be filled at different levels depending on the education, experience, and qualifications of the selected candidate. You will report to the Principal Investigator.
Responsibilities*
Genomic Data Analysis (35%)
  • Process, quality control, and analyze large-scale whole-genome sequencing datasets generated through TOPMed and related studies
  • Support analyses of both short-read and long-read sequencing data, including variant discovery, structural variation, haplotype analysis, and emerging applications enabled by long-read technologies
  • Integrate genomic results with clinical, phenotypic, and epidemiologic datasets

Single-Cell and Functional Genomics (30%)
  • Analyze single-cell RNA-seq and related single-cell multiomic datasets
  • Perform cell-type annotation, differential expression analyses, integration across studies, trajectory analyses, and biological interpretation
  • Develop and maintain reproducible workflows for single-cell data processing and analysis

Pipeline and Software Development (20%)
  • Develop, maintain, and optimize scalable bioinformatics workflows and analytical pipelines
  • Implement reproducible computational methods using workflow management systems such as Nextflow, Snakemake, or WDL
  • Support analyses on high-performance computing and cloud-based environments

Research Collaboration and Scientific Contributions (15%)
  • Collaborate with faculty investigators, staff scientists, trainees, and external research partners
  • Contribute to manuscripts, reports, grant applications, and scientific presentations
  • Remain current with emerging technologies and analytical methods in genomics and computational biology

Required Qualifications*
  • Ph.D. in Bioinformatics, Computational Biology, Genetics, Biostatistics, Computer Science, Biomedical Informatics, or a related field with 2-5 years of related experience (1-2 years for Intermediate). Candidates with a Master's or Bachelor's degree may be considered with substantial relevant professional experience
  • Demonstrated experience analyzing high-throughput sequencing data
  • Strong programming skills in Python, R, or related scientific programming languages
  • Experience working in Linux/Unix computing environments
  • Experience developing reproducible computational analyses and workflows
  • Strong analytical, organizational, and problem-solving skills
  • Excellent written and verbal communication skills
  • Ability to work effectively both independently and as part of a multidisciplinary research team

Desired Qualifications*
Experience in one or more of the following areas would strengthen an application:
  • Single-cell RNA-seq or other single-cell omics analyses
  • Long-read sequencing technologies, including PacBio HiFi and Oxford Nanopore platforms
  • Whole-genome sequencing analyses and variant interpretation
  • Structural variant discovery and genome assembly-related analyses
  • Large-scale genomic resources such as TOPMed, All of Us, UK Biobank, or other population-based studies
  • Cloud computing environments such as Terra, AWS, or Google Cloud
  • Workflow development using Nextflow, Snakemake, Cromwell/WDL, or related frameworks
  • Containerization technologies such as Docker or Apptainer/Singularity
  • Multi-omics data integration
  • Scientific publications, open-source software development, or other evidence of research leadership and impact

Why Work at Michigan?
In addition to a career filled with purpose and opportunity, The University of Michigan offers a comprehensive benefits package to help you stay well, protect yourself and your family and plan for a secure future. Benefits include:
  • Generous time off, including family leave
  • A retirement plan that provides two-for-one matching contributions with immediate vesting
  • Many choices for comprehensive health insurance, dental, vision
  • Life insurance
  • Long-term disability coverage
  • Flexible spending accounts for healthcare and dependent care expenses

How You'll Grow
This position provides you the opportunity to work at the forefront of genomic science within one of the largest and most influential precision medicine programs in the world. You will have access to exceptional genomic resources, advanced computational infrastructure, and a highly collaborative scientific environment, while contributing to research that advances our understanding of human health and disease.
Modes of Work
This is a hybrid position and requires residence within commuting distance to the Ann Arbor campus. 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 .
Underfill Statement
This position may be underfilled at a lower classification depending on the qualifications of the selected candidate.
Senior - $88,744 - $109,625
Intermediate - $69,906 - $86,355
Additional Information
This position will start as a three-year term-limited position. This position is funded by a five-year federal contract with three years remaining. The project has received continuous funding since 2015, and we expect this to continue beyond the current contract term.
Background Screening
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third-party administrator to conduct background checks. Background checks are performed in compliance with the Fair Credit Reporting Act.
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 any time after the minimum posting period has ended.
U-M EEO Statement
The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.
Job Detail
Job Opening ID
281676
Working Title
Bioinformatics Scientist / Computational Biologist
Job Title
Bioinfo-Comput Biologist Sr
Work Location
Ann Arbor Campus
Ann Arbor, MI
Modes of Work
Hybrid
Full/Part Time
Full-Time
Regular/Temporary
Regular
FLSA Status
Exempt
Organizational Group
School Pub Health
Department
Biostatistics Department
Posting Begin/End Date
8/14/2026 - 9/13/2026
Salary
$88,744.00 - $109,625.00
Career Interest
Research

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About University of Michigan

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The University of Michigan (U-M), based in Ann Arbor, MI, US, is one of America's most esteemed institutions in higher education. Established in 1817, it presides in the industry of education and research, providing a range of services including undergraduate, graduate, and professional education programs. Complementing this is an extensive research activity that has significantly contributed to various fields, from healthcare to engineering, humanities to sports. Upholding its mission "to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values", U-M consistently ranks among the top universities globally, a testament to its tradition of excellence in learning and research, and a deep commitment to innovation and discovery.

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Company size

10,000+ Employees

Headquarters location

Ann Arbor, MI, US

Year founded

1817

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