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Spatial Transcriptomics Omics Jobs in Michigan (NOW HIRING)

... spatial transcriptomics, neurophysiology, and advanced computational approaches. The lab is ... omics workflows. Applicants must be able to apply these methods accurately and independently ...

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 job categories do people searching Spatial Transcriptomics Omics jobs in Michigan look for? The top searched job categories for Spatial Transcriptomics Omics jobs in Michigan are:
What cities in Michigan are hiring for Spatial Transcriptomics Omics jobs? Cities in Michigan with the most Spatial Transcriptomics Omics job openings:
Assistant Scientist / Assistant Professor - Computational Biology

Assistant Scientist / Assistant Professor - Computational Biology

Henry Ford Medical Group

Detroit, MI

Other

Posted 15 days ago


Job description

Henry Ford Health

Henry Ford Health (HFH) in Detroit, Michigan, is one of the nation's leading comprehensive health systems, recognized for excellence in clinical care, research, and education. The Center for Cutaneous Biology and Immunology (CCBI) is a dynamic, multidisciplinary research program dedicated to advancing our understanding of skin biology and immunology, cancer immunology, and the functional genomics that govern immune cell behavior in cancer as well as autoimmune and inflammatory diseases. Our team fosters an innovative, collaborative, diverse, and open-minded research environment in partnership with Michigan State University. We are supported by multiple NIH-funded grants and active communities of immunologists, molecular biologists, biochemists, data scientists, physician scientists, and computational biologists. Our mission is to advance translational research that leads to meaningful improvements in clinical care.

Position Description

We invite applications for an Assistant Professor / Assistant Scientist with expertise in computational biology, statistical genetics, genomics, and AI-driven medicine. We seek a highly motivated individual who develops and applies state-of-the-art computational methods to complex, large-scale biological datasets. The successful candidate will contribute to high-impact translational research programs and lead independent research efforts, and will hold a joint faculty appointment (Assistant Scientist) with Michigan State University as part of the HFH-MSU Health Sciences partnership.

Key Responsibilities

  • Develop and apply computational, statistical, and AI/ML approaches to analyze diverse biological datasets, including:
    • GWAS, whole-genome/exome sequencing
    • DNA methylation and epigenomic profiling
    • Bulk and single-cell RNA-seq, spatial transcriptomics
    • ATAC-seq (bulk and single-cell), proteomics, CyTOF, and IMC
    • Histological and radiological imaging data
    • Clinical and epidemiological datasets
  • Lead independent research projects and contribute to collaborative team science initiatives.
  • Pursue external funding (e.g., NIH, NSF, foundations) to support research programs.
  • Mentor trainees and collaborate closely with investigators across HFH and Michigan State University.

Required Qualifications

  • PhD in biostatistics, bioinformatics, computational biology, computer science, or a related discipline.

  • Strong research track record in genetics, multi-omics integration, and/or AI applications to biological or clinical data, as demonstrated by peer-reviewed publications and conference presentations.

  • Demonstrated ability-or strong potential-to secure external research funding.

  • Proficiency in programming and analytical languages/platforms (e.g., R, Python, TensorFlow, PyTorch).

  • Experience working in Unix/Linux environments, including shell scripting (Bash, awk, sed).

  • Familiarity with tools for genomic, epigenomic, transcriptomic, and proteomic analysis, including next-generation sequencing pipelines (DNA-seq, RNA-seq, ATAC-seq, ChIP-seq).

  • Experience with single-cell and spatial transcriptomics, eQTL/pQTL analysis, and multimodal data integration.

  • Familiarity with imaging analytics (e.g., spatial transcriptomics, H&E, IMC, radiological imaging).

  • Experience in human subjects research, healthcare data, epidemiology, or biomedical applications.

  • Excellent communication, interpersonal, organizational, and collaborative skills, with the ability to work effectively with colleagues of diverse technical and scientific backgrounds.

How to Apply:

Please submit your CV, cover letter, and research statement (past accomplishments, current work, and future research vision) to:

Dr. Qing-Sheng Mi, MD, PhD

Director, Center for Cutaneous Biology and Immunology (CCBI)

Email: qmi1@hfhs.org

Equal Employment Opportunity/Affirmative Action Employer

Henry Ford Health is committed to the fair and equitable treatment of all individuals and prohibits discrimination based on race, color, creed, religion, age, sex, national origin, disability, veteran status, marital or family status, gender identity, sexual orientation, height, weight, genetic information, or any other protected category in accordance with federal and state laws.

Additional Information
  • Organization: Henry Ford Medical Group
  • Department: Dermatology - New Center Det
  • Shift: Day Job
  • Union Code: Not Applicable