Position DescriptionWe 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, PhDDirector, Center for Cutaneous Biology and Immunology (CCBI)
Email:
[email protected] 
