Field of Study:
Engineering, Neuroscience, Computational and Molecular Biology, Anesthesiology
Department:
Anesthesiology
Rank of Student:
Freshman - Junior
Desired Majors:
Any life science major or engineering major with an interest in biology
Hours per Week:
10
Compensation Type:
Academic Credit,
Voluntary Experience
Application Deadline:
Contact:
hamdy.elsayed-awad@osumc.edu, amar.dabbagh@osumc.edu
Private
Public
Project Description
We are seeking a highly motivated undergraduate student to join a research project focused on preventing paralysis that can occur after thoracic aortic aneurysm repair surgery. The project uses a validated mouse model of spinal cord ischemia and reperfusion injury to study the delayed molecular events that lead to loss of motor function. The central component of this position is analyzing high-resolution spatial transcriptomics data generated by the Visium HD platform. The student will help map differentially expressed genes across spinal cord regions, identify patterns of inflammation and neuronal injury, and contribute to the discovery of potential therapeutic targets.
The student will work directly with spatial transcriptomics datasets, performing tasks such as data preprocessing, quality control, visualization of spatial gene expression, and differential expression analysis. The role will provide training in R, Seurat-based workflows, and basic bioinformatic pipelines. Depending on interest, the student may additionally learn complementary wet-lab techniques used to generate validation data, including tissue sectioning, immunohistochemistry, and imaging. The student will participate in weekly lab meetings, gain experience with research documentation, and contribute to the interpretation and presentation of results.
The student will work directly with spatial transcriptomics datasets, performing tasks such as data preprocessing, quality control, visualization of spatial gene expression, and differential expression analysis. The role will provide training in R, Seurat-based workflows, and basic bioinformatic pipelines. Depending on interest, the student may additionally learn complementary wet-lab techniques used to generate validation data, including tissue sectioning, immunohistochemistry, and imaging. The student will participate in weekly lab meetings, gain experience with research documentation, and contribute to the interpretation and presentation of results.
Additional Information
The weekly time commitment and schedule are flexible and can be adjusted around the student’s coursework. Students will have opportunities to remain in the lab longer term and work toward poster presentations/publications.
Required Applicant Information
Resume/CV, most recent transcript, and letter of interest
Required or Desired Skills
Required:
Strong interest in computational biology, neuroscience, or biomedical science
Willingness to learn R (or possibly Python) for data analysis
Optional:
Prior experience with programming, especially R or Python
Familiarity with transcriptomics, sequencing data, or Seurat
Basic understanding of molecular biology or neurobiology
Previous experience working with large datasets or quantitative analysis
Strong interest in computational biology, neuroscience, or biomedical science
Willingness to learn R (or possibly Python) for data analysis
Optional:
Prior experience with programming, especially R or Python
Familiarity with transcriptomics, sequencing data, or Seurat
Basic understanding of molecular biology or neurobiology
Previous experience working with large datasets or quantitative analysis
Faculty Member Lead:
Hamdy Elsayed-Awad
Starting Semester:
Spring
Length of Project (in semesters):
4