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Spatial Transcriptomics Omics Jobs in Alabama (NOW HIRING)

... spatial transcriptomics datasets. * Develop and implement bioinformatics pipelines for variant calling, structural variant detection, transcriptome profiling, and integrative multi-omics analyses.

Spatial Transcriptomics Omics information

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

To thrive as a Spatial Transcriptomics Specialist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree in a relevant field. Familiarity with high-throughput sequencing platforms, spatial omics technologies, and data analysis tools like R or Python is essential, along with experience using laboratory automation systems. Attention to detail, problem-solving abilities, and effective interdisciplinary communication are crucial soft skills for this role. These skills ensure accurate experimental design, robust data interpretation, and successful collaboration in cutting-edge biological research.

What are some common challenges faced by professionals in Spatial Transcriptomics Omics, and how can they be addressed?

Professionals working in Spatial Transcriptomics Omics often encounter challenges such as managing and interpreting large, complex datasets, integrating multi-omics data, and keeping pace with rapidly evolving technologies. Effective collaboration with bioinformaticians, pathologists, and laboratory technicians is essential to ensure high-quality results. Staying updated with the latest analytical tools and participating in cross-disciplinary training can help overcome these challenges and enhance both research quality and career growth.

What is spatial transcriptomics in omics research?

Spatial transcriptomics is a cutting-edge technology in the field of omics that allows researchers to measure and map gene expression within the spatial context of intact tissue sections. This means scientists can see which genes are active in specific locations of a tissue, preserving the spatial relationships between cells. By combining spatial information with transcriptomic data, researchers gain deeper insights into tissue organization, cellular interactions, and disease mechanisms. This approach is especially valuable for understanding complex tissues like tumors or brain structures.

What is the difference between Spatial Transcriptomics Omics vs Spatial Transcriptomics Technician?

AspectSpatial Transcriptomics OmicsSpatial Transcriptomics Technician
Required CredentialsAdvanced degrees (Master's/PhD) in molecular biology, genomics, or related fieldsAssociate's or Bachelor's degree in biology, biotechnology, or related fields
Work EnvironmentResearch labs, biotech companies, academic institutionsLaboratories, research facilities, biotech companies
Industry UsageResearch and development, data analysis, method developmentSample preparation, data collection, equipment operation

Spatial Transcriptomics Omics professionals focus on data analysis, method development, and research, often requiring advanced degrees. In contrast, Spatial Transcriptomics Technicians handle sample preparation and operate equipment, typically with a technical diploma or bachelor's degree. Both roles are essential in the spatial transcriptomics industry but differ in responsibilities and qualifications.

What are popular job titles related to Spatial Transcriptomics Omics jobs in Alabama? For Spatial Transcriptomics Omics jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Spatial Transcriptomics Omics jobs in Alabama look for? The top searched job categories for Spatial Transcriptomics Omics jobs in Alabama are:
Infographic showing various Spatial Transcriptomics Omics job openings in Alabama as of May 2026, with employment types broken down into 86% Full Time, 5% Part Time, 5% Contract, and 4% Nights. Highlights an 67% Physical, 29% Hybrid, and 4% Remote job distribution.
Research Assistant Professor-Genomic Sequencing Data Analysis

Research Assistant Professor-Genomic Sequencing Data Analysis

Tuskegee University

On-site

Full-time

Posted 22 days ago


Job description

Position Details
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Position Information
Position Title
Research Assistant Professor-Genomic Sequencing Data Analysis
Job Summary
We are seeking a highly skilled and motivated Research Assistant Professor with expertise in genomic sequencing data analysis to join our multidisciplinary research team. The successful candidate will lead computational and statistical analyses of large-scale genomic datasets, including whole-genome, whole-exome, and transcriptomic sequencing, to advance projects in cancer biology, precision medicine, and related biomedical fields. This position offers the opportunity to develop independent research while contributing to collaborative team science.
Essential Job Duties
  • Perform high-quality computational analysis of next-generation sequencing (NGS) data, including short and long-read whole-genome, whole-exome, RNA-seq, and spatial transcriptomics datasets.
  • Develop and implement bioinformatics pipelines for variant calling, structural variant detection, transcriptome profiling, and integrative multi-omics analyses.
  • Apply statistical and machine learning approaches to identify genomic alterations, biomarkers, and functional networks.
  • Collaborate with wet-lab scientists to integrate genomic data with experimental results.
  • Contribute to manuscript preparation, figure generation, and presentation of findings at scientific conferences.
  • Write and contribute to competitive grant applications, providing preliminary data and computational expertise.
  • Mentor graduate students, postdoctoral fellows, and research staff in computational genomics.
  • Maintain data management, quality control, and reproducibility standards in accordance with institutional and funding agency guidelines,

Preferred Qualifications
  • Ph.D. or equivalent degree, with postdoctoral training in bioinformatics, computational biology, genomics, computer science, statistics, or related field.
  • Demonstrated expertise in NGS data analysis, including quality control, alignment, variant calling, and downstream interpretation.
  • Proficiency with bioinformatics tools (e.g., GATK, samtools, bcftools, STAR, HISAT2, Cell Ranger, Seurat) and programming languages (e.g., Python, R, Bash).
  • Experience working with high-performance computing and cloud-based analysis platforms.
  • Experience with cancer genomics, single-cell and spatial transcriptomics, or epigenomic data analysis.

Physical Demands
FLSA
Exempt
Status
Full-Time
Skills and Attributes
  • Familiarity with database development, workflow management systems (e.g., Nextflow, Snakernake), and reproducible research practices (e.g., Docker, Git).
  • Strong track record of peer-reviewed publications in genomic data analysis.
  • Excellent problem-solving, organizational, and communication skills.
  • Ability to work effectively in multidisciplinary research teams.

Posting Detail Information
Posting Number
Will this position required travel?
yes
Will this position required night, weekend, and after hour work?
yes
Will this positon be supported using grants or contract funding?
yes
Number of Vacancies
1
Desired Start Date
Position End Date (if temporary)
Open Date
04/07/2026
Close Date
Open Until Filled
No
Special Instructions Summary
Each applicant, including all current employees, must complete and submit the following documents:
  • Tuskegee University employment application
  • Cover Letter
  • Resume/CV
  • Recommendation letters
  • Copies of unofficial transcripts.
  • Please note that official transcripts(s) will be required upon hire

Quick Link for Internal Postings
https://tuskegee.peopleadmin.com/postings/3659