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Computational Spatial Transcriptomics Jobs in Arizona

Computational Spatial Transcriptomics information

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.
What are popular job titles related to Computational Spatial Transcriptomics jobs in Arizona? For Computational Spatial Transcriptomics jobs in Arizona, the most frequently searched job titles are:
Postdoctoral Researcher - Computational biology/Cancer bioinformatics (Full Time)

Postdoctoral Researcher - Computational biology/Cancer bioinformatics (Full Time)

University of Arizona

Tucson, AZ • On-site

Full-time

Medical, Dental, Vision, Life, PTO

Posted 7 days ago


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Job description

Postdoctoral Researcher - Computational biology/Cancer bioinformatics (Full Time)
Posting Number
req26025
Department
Cancer Center Division
Department Website Link
https://cancercenter.arizona.edu/
Location
Tucson Campus
Address
1501 N. Campbell Ave, Tucson, AZ 85719 USA
Position Highlights
The Theodorescu Lab within the University of Arizona Cancer Center (UACC) and Padi Labs within the Department of Molecular and Cellular Biology are looking to hire a joint postdoctoral researcher with a strong background in computational biology and/or cancer bioinformatics. This project will be focused on integrating rich, multimodal 'omics data from cell lines and animal models, with the goal of identifying mechanisms leading to transformation and cancer. To identify such cancer-driving effects, we combine genomics, proteomics, and spatial transcriptomics data generated in the Theodorescu Lab with techniques for network inference, epigenetic rewiring, and dynamic modeling developed in the Padi Lab. Examples of the type of work that will be undertaken can be seen by our papers by Chen (Nature. 2025 Jun;642(8069):1041-1050), Abdel-Hafiz (Nature. 2023 Jul;619(7970):624-631), Gouin (Nature Commun. 2021; 12;12(1)), Ben Guebila (Genome Biology. 2023; 24(1):45) and Yang (Journal of Clinical Investigation. 2025; 135(7)). Our final goal is to identify novel biomarkers and interventions for cancer that will improve patient outcomes.
This individual would join two vibrant groups that closely collaborate to bridge the gap between innovative cancer research and state-of-the-art computational modeling. The successful candidate will be a driven, creative, team-oriented individual with an aptitude for quantitative/informatic methods and a passion for helping to discover fundamental cancer biology mechanisms that have potential clinical impact and thus can be moved eventually towards a clinical setting. We employ a wide variety of computational and experimental approaches and seek individuals with a strong understanding of both bioinformatics and molecular biology. Experience gained in our laboratory will help the candidate to become competitive for permanent positions in either academia or industry. We welcome applications from both recent PhD or MD/PhD recipients and individuals seeking additional postdoctoral training. For more information, please visit: https://cancercenter.arizona.edu/person/dan-theodorescu-md-phd and https://www.padilab.com.
Outstanding U of A benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members; access to UA recreation and cultural activities; and more!
The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocation services, please click here.
Duties & Responsibilities
  • Design and perform quantitative data analysis. Keep detailed record of codebase with documentation and share the results with the Principal Investigators.
  • Develop, adapt, and implement new research techniques and algorithms.
  • Analyze, interpret, present, and interpret the data clearly and accurately.
  • Perform routine and complex data analysis procedures throughout training period.
  • Assist in preparation of grant proposals with the PIs but is not responsible for generating grant funds.
  • Participate in publications and presentations as author or co-author.
  • Meet with both PIs on a regular basis to discuss research progress and plans.
  • May be asked to write small grant proposals or NRSA/T32 applications.
  • Spends about 75% of time on computational analysis and 25% of time on writing articles/analyzing data/online research.

Knowledge,Skills, and Abilities:
  • Ability to work semi-independently on research projects within an area of specialization.
  • Thorough technical and theoretical knowledge of research projects and the objectives to be accomplished during this post-doctoral appointment.
  • Demonstrated aptitude to perform quantitative analyses, generate reproducible code, and interpret results in a biological context.
  • Strong understanding of both bioinformatics andmolecular biology.

Minimum Qualifications
  • Doctorate(PhD or MD/PhD) in computational biology, physics, math, computer science, orrelated field.

Preferred Qualifications
  • Outstanding publication record from prior graduate and/or postgraduate training and/or existing extramural funding.

FLSA
Exempt
Full Time/Part Time
Full Time
Number of Hours Worked per Week
40
Job FTE
1.0
Work Calendar
Fiscal
Job Category
Research
Benefits Eligible
Yes - Full Benefits
Rate of Pay
NIH salary guidelines, Depends on Experience
Compensation Type
salary at 1.0 full-time equivalency (FTE)
Type of criminal background check required:
Name-based criminal background check (non-security sensitive)
Number of Vacancies
1
Target Hire Date
Expected End Date
Contact Information for Candidates
Dr Megha Padi,mpadi@arizona.edu
Open Date
5/15/2026
Open Until Filled
Yes
Documents Needed to Apply
Curriculum Vitae (CV) and Cover Letter
Special Instructions to Applicant
Application: The online application should be completed in its entirety. Blank or missed information may be considered an incomplete submission.
Cover Letter: Should clearly indicate how your skills and professional employment experience meet the Minimum and the Preferred qualifications (if applicable).
Notice of Availability of the Annual Security and Fire Safety Report
In compliance with the Jeanne Clery Campus Safety Act (Clery Act), each year the University of Arizona releases an Annual Security Report (ASR) for each of the University's campuses.Thesereports disclose information including Clery crime statistics for the previous three calendar years and policies, procedures, and programs the University uses to keep students and employees safe, including how to report crimes or other emergencies and resources for crime victims. As a campus with residential housing facilities, the Main Campus ASR also includes a combined Annual Fire Safety report with information on fire statistics and fire safety systems, policies, and procedures.
Paper copies of the Reports can be obtained by contacting the University Compliance Office at cleryact@arizona.edu.

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