Assistant Scientist: AI-Driven Genomics & Computational Biology

Henry Ford Health; Detroit (MI); On-site; USD 130,000 - 180,000; Full time

Job summary

Henry Ford Health in Detroit, MI, invites applications for an Assistant Professor/Assistant Scientist in computational biology with strong ties to Michigan State University. The role focuses on developing state-of-the-art methods for large-scale biological data and leading translational research within HFH/MSU collaborations.

The successful candidate will secure external funding, mentor trainees, and contribute to high-impact programs spanning genomics, multi-omics, and AI-driven medicine.

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.
• Demonstrated ability—or strong potential—to secure external research funding.
• Proficiency in R, Python, TensorFlow, PyTorch; Unix/Linux environments; shell scripting.

Responsibilities

• Develop and apply computational, statistical, and AI/ML approaches to analyze diverse biological datasets.
• Lead independent research projects and collaborate with HFH and MSU investigators.
• Pursue external funding (e.g., NIH, NSF, foundations) to support research programs.
• Mentor trainees and foster collaboration across HFH and MSU.

Skills

Computational biology

Genomics

AI/ML in biology

Multi-omics integration

Data analysis

Programming (R, Python)

Education

PhD in biostatistics, bioinformatics, computational biology, computer science, or related

Tools

R

Python

TensorFlow

PyTorch

Unix/Linux

Job description

Henry Ford Health in Detroit, MI, invites applications for an Assistant Professor/Assistant Scientist in computational biology with strong ties to Michigan State University. The role focuses on developing state-of-the-art methods for large-scale biological data and leading translational research within HFH/MSU collaborations.

The successful candidate will secure external funding, mentor trainees, and contribute to high-impact programs spanning genomics, multi-omics, and AI-driven medicine.