Assistant Scientist / Assistant Professor - Computational Biology

At Henry Ford Health, we're committed to advancing health and improving lives for the millions of people we serve across Michigan and around the world. As one of the nation's leading academic health systems, we provide a comprehensive continuum of care that includes primary and preventive services, specialty and complex care, virtual care, pharmacy, home health, eye care, health insurance, and more. With 12 hospitals and hundreds of ambulatory care locations, including former Ascension Southeast Michigan and Flint Region facilities, our growing network expands access to exceptional care in the communities we serve.

Headquartered in Detroit, Henry Ford Health is helping shape the future of healthcare through the transformative Future of Health: Detroit initiative, a $3 billion investment that is redefining our academic healthcare campus and advancing innovation, research, education, and community impact.

Our work is grounded in purpose, collaboration, and belonging. We empower team members to grow their careers, contribute innovative ideas, and make a meaningful difference every day. Whether you're caring for patients, supporting operations, conducting research, or driving new solutions, you'll be part of a team united by a shared mission: delivering exceptional care, advancing health outcomes, and building healthier communities for all.

Job Description

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.

 

Qualifications

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.