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Computational Spatial Transcriptomics Jobs in Blaine, MN

Computational Spatial Transcriptomics information

See Blaine, MN salary details

$42

$56

$76

How much do computational spatial transcriptomics jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for computational spatial transcriptomics in Blaine, MN is $56.88, according to ZipRecruiter salary data. Most workers in this role earn between $48.56 and $76.15 per hour, depending on experience, location, and employer.

What are some typical challenges faced when working in computational spatial transcriptomics, and how can new team members prepare for them?

Professionals in computational spatial transcriptomics often encounter challenges related to handling and analyzing large, complex datasets that combine spatial and gene expression information. Integrating data from different technologies and ensuring data quality can be demanding, requiring strong programming skills and familiarity with bioinformatics pipelines. New team members can prepare by strengthening their skills in statistical analysis, programming languages like Python or R, and staying updated on the latest spatial transcriptomics techniques. Collaborating closely with experimental biologists and data scientists is also key to overcoming these challenges and driving successful research outcomes.

What is the difference between Computational Spatial Transcriptomics vs Computational Biologist?

AspectComputational Spatial TranscriptomicsComputational Biologist
Required CredentialsAdvanced degrees in bioinformatics, computational biology, or related fields; experience with spatial data analysisTypically a PhD or Master's in biology, bioinformatics, or related disciplines; strong programming skills
Work EnvironmentResearch labs, biotech companies, academic institutions focusing on spatial genomicsResearch institutions, biotech firms, academia working on biological data analysis
Industry UsageSpecialized in spatial transcriptomics techniques and data interpretationBroad biological data analysis across various fields

Computational Spatial Transcriptomics focuses on analyzing spatial gene expression data within tissues, requiring specialized skills in spatial data processing. In contrast, Computational Biologists work on a wider range of biological data types. While both roles involve bioinformatics expertise, the former emphasizes spatial data analysis techniques specific to transcriptomics.

What is computational spatial transcriptomics?

Computational spatial transcriptomics is a field that combines advanced computational methods with spatial transcriptomics, a technique that measures gene expression within the physical context of tissue samples. It involves processing and analyzing large datasets to map where specific genes are active within tissues, helping researchers understand how cells interact and function in their native environments. This approach is crucial for studies in developmental biology, cancer research, and neuroscience, as it provides insights into cellular organization and tissue architecture. Computational tools help extract meaningful patterns from complex data, enabling discoveries that were previously impossible with traditional methods.

What are the key skills and qualifications needed to thrive as a Computational Spatial Transcriptomics Scientist, and why are they important?

To excel in Computational Spatial Transcriptomics, you need a strong background in bioinformatics, genomics, and statistical data analysis, typically supported by advanced degrees in computational biology or related fields. Familiarity with programming languages (such as R and Python), spatial transcriptomics platforms (like 10x Genomics Visium), and high-throughput sequencing data analysis tools is essential. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for interpreting complex datasets and collaborating with multidisciplinary teams. These competencies ensure accurate data interpretation, innovative research, and successful integration of spatial transcriptomics insights into biological and clinical applications.
Post-Doctoral Associate - Bioinformatics & Computational Biology

Post-Doctoral Associate - Bioinformatics & Computational Biology

University of Minnesota

Minneapolis, MN

$62K - $75K/yr

Full-time

Medical, Dental, Life

Posted 6 days ago


Job description

About the Job
 

Required Qualifications:
A PhD degree in related field (Bioinformatics, Computer Science, Statistics, etc.) obtained in the last 1~2 years.
Strong quantitative data analysis background (machine learning, biostatistics, etc.) and/or computational genomics/genetics experiences (spatial transcriptomics, single-cell sequencing, high-throughput omics sequencing data analysis, TWAS/GWAS, etc.) or other relevant areas.
Strong programming skills: (e.g., R, Python, and Unix Shell).
Quick learning capability for new technologies and analytical methods
Strong communication and interpersonal skills and a track record of collaborative work in multidisciplinary research environment.
Job description:
Zhus lab is a dry lab. The research interests are mainly focused on the novel computational methodology design and integrative multi-modality data analysis to (1) enhance the spatial profiling technology and (2) screen the pathogenic upstream regulator.
Responsibilities:
Develop novel computational methods to enhance the power of spatial-omics technology.
Develop novel computational methods to advance understanding of the complex genetic diseases, e.g., fatty liver disease, diabetes, etc.
Conduct rigorous and reproducible integrative multi-modality data analysis (generated from spatially resolved sequencing, single-cell sequencing, long-read and short-read bulk sequencing, etc.) to shed lights on the coordinated biological regulatory mechanism from different omics layers.
Publish high-impact factor papers and give presentations of novel research findings in academic journals and conferences.
Manage and maintain software/database for long-standing user support.

Pay and Benefits
 

Pay Range: $62,232 - 75,564 (follows NIH stipend levels); depending on education/qualifications/experience

Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility.

  • Competitive wages, paid holidays, and generous time off
  • Continuous learning opportunities through professional training
  • Medical, dental, and pharmacy plans
  • Healthcare and dependent care flexible spending accounts
  • University HSA contributions
  • Disability and life insurance
  • Employee wellbeing program
  • Financial counseling services
  • Employee Assistance Program with eight sessions of counseling at no cost
How To Apply
 

Applications must be submitted online.  To be considered for this position, please click the Apply button and follow the instructions.  You will be given the opportunity to complete an online application for the position and attach (all three required) -

  • cover letter
  • CV
  • the name and contact information for three professional references

Additional documents may be attached after application by accessing your "My Job Applications" page and uploading documents in the "My Cover Letters and Attachments" section.

To request an accommodation during the application process, please e-mail employ@umn.edu or call (612) 624-UOHR (8647).

Diversity
 

The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission.  The University is committed to attracting and retaining employees with varying identities and backgrounds.

The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression.  To learn more about diversity at the U:  http://diversity.umn.edu

Employment Requirements
 

Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.

About University of Minnesota
 

The University of Minnesota, Twin Cities (UMTC)

The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation's most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.

At the University of Minnesota, we are proud to be recognized by the Star Tribune as a Top Workplace for 2021, as well as by Forbes as Best Employers for Women and one of Americas Best Employers (2015, 2018, 2019, 2023), Best Employer for Diversity (2019, 2020), Best Employer for New Grads (2018, 2019), and Best Employer by State (2019, 2022).