The Wythe Lab is looking to hire a full-time scientist with experience in 3D imaging and image analysis to lead a newly funded NIH UC2 grant initiative on imaging the nerve-vessel interface in the setting of osteoarthritis. Experience in confocal imaging is essential, and expertise in lightsheet imaging and post-acquisition image analysis (IMARIS, AMIRA, Arivis, ImageJ/Fiji, Neurolucida, etc.) would be desirable. A background in neuroscience, immunology, or vascular biology or skeletal development or injury is attractive.

The position would be expected to establish and optimize existing imaging protocols (CLARITY, EZCLear, iDISCO, etc) for 3D imaging, image analysis within the lab, while also analyzing data and making figures and writing text for manuscripts and preprints to create figures to visualize their data. The hire would be expected to train others within the lab in these imaging methods, deal with basic mouse colony maintenance as needed for the project, with a focus on imaging.

Candidates will also perform general lab duties (ordering, stocking, etc), attend and present at lab meeting and grant consortia events and meetings. Standard immunohistochemistry, histology, and other imaging approaches and analysis will also apply.

All team members meet 1 on 1 with the PI weekly to summarize their progress and troubleshoot their projects, and their attendance at our weekly lab meeting is expected, as will be semi frequent (~ every 2-3 months) presentations on their data, as well as infrequent journal club presentations and attendance at NIH RE-JOIN/HEAL consortia events and meetings.

The applicant may be expected to peer review manuscripts, replicate findings of others in the lab, help with presentations, or perform standard biological experiments mice and/or imaging modalities (micro-CT, confocal, LSFM, etc.).

Minimum Requirements
Education: Doctoral degree

Preferred Skills

Education: A Ph.D. in immunology, skeletal development or injury, vascular biology, or neuroscience, and experience working with mice, or extensive relevant work experience in these fields.

Experience: Expertise with post-acquisition imaging processing is essential. Knowledge of Adobe suite (illustrator, photoshop)
Evidence of productivity, such as peer reviewed publications, or preprints or imaging analysis pipeline development tools are preferred.

Familiarity with PRISM/graphpad is beneficial

Physical Demands
This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs.

Application Instructions: Please apply through Workday and complete an application online. Include the following documents:

• A CV/resume

• A cover letter

All documents can be loaded into the resume submission field, multiple documents can be submitted into this one field. Internal applicants must apply through their UVA Workday profile. Incomplete applications will not be considered.

For questions about the application process, please contact Margaret Weeks , Academic Recruiter. Before a formal offer of employment is extended, the selected candidate will undergo a background check per university policy.

COVID Vaccination Requirement and Guidelines

Please visit the UVA COVID-19 Job Requirements and Guidelines webpage prior to applying for current information regarding vaccination requirements and guidelines for employment at UVA.

The University of Virginia, i ncluding the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician’s Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff. We believe diversity is excellence expressing itself through every person's perspectives and lived experiences. We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information.