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Biology Coding Jobs in Michigan (NOW HIRING)

Absopure

Quality Assurance Technician

Plymouth, MI

Production checks, codes, labels, fill volumes, torque test, caps, leakers, etc. * Sampling for ... Requires a Bachelor's degree in Chemistry, Biology or related science or 2-4 years of related ...

University of Michigan

RESEARCH FELLOW

Ann Arbor, MI · On-site

... coding genome, with a focus on metabolic traits. We combine statistical genetics, single-cell and single-nucleus multi-omics, and computational genomics to translate GWAS signals into biology. Our ...

Belcan

Laboratory Technician I

Flint, MI

$22/hr

Flint, MI Area Code: 810 ZIP Code: 48505 Start Date: Right Away Keywords: #Flintjobs ... biological or chemical analytical tests according to standard procedures. * Assists higher level ...

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$156.4K

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How much do biology coding jobs pay per year?

As of May 31, 2026, the average yearly pay for biology coding in Michigan is $156,367.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,500.00 and $199,400.00 per year, depending on experience, location, and employer.

What is a Biology Coding job?

A Biology Coding job involves using programming skills to analyze biological data, develop software tools, and create algorithms for applications like genomics, bioinformatics, and computational biology. Professionals in this field often use languages like Python, R, or MATLAB to process large datasets, automate experiments, and model biological systems. These roles are common in healthcare, biotechnology, research institutions, and pharmaceutical industries.

What are the key skills and qualifications needed to thrive in the Biology Coding position, and why are they important?

To thrive in a Biology Coding role, you need a solid background in biological sciences combined with strong programming skills, typically evidenced by a degree in biology, bioinformatics, or a related field, and proficiency in languages such as Python or R. Familiarity with data analysis platforms, bioinformatics tools, and experience with databases like GenBank or BLAST are often required. Attention to detail, analytical thinking, and effective communication are essential soft skills for collaborating with multidisciplinary teams. These competencies are crucial for accurately translating biological data into actionable insights and supporting research and development initiatives.

What are the typical daily tasks for someone working in Biology Coding?

Professionals in Biology Coding commonly spend their days analyzing large biological datasets, developing scripts or software to automate repetitive tasks, and collaborating with researchers to interpret data findings. They may also clean and prepare raw data, create data visualizations, and maintain documentation to ensure reproducibility of analyses. Interfacing with both scientists and computational teams is a key part of the job, making clear communication and teamwork vital. This dynamic role offers a mix of independent problem-solving and collaborative project work, providing a stimulating and impactful environment for growth.
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Biology Coding jobs near you
Infographic showing various Biology Coding job openings in Michigan as of May 2026, with employment types broken down into 1% Internship, 52% Full Time, 36% Part Time, 2% Temporary, and 9% Contract. Highlights an 49% Physical, 6% Hybrid, and 45% Remote job distribution, with an average salary of $156,367 per year, or $75.2 per hour.
Assistant Scientist / Assistant Professor - Computational Biology

Assistant Scientist / Assistant Professor - Computational Biology

Henry Ford Medical Group

Detroit, MI

Other

Posted 16 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

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