The laboratory of Chongzhi Zang at the Center for Public Health
Genomics, University of Virginia (UVA) is seeking to fill multiple
Postdoctoral Research Associate positions in the broad field of
bioinformatics and computational biology. The research program in
the lab focuses on developing computational methodologies and
designing integrative data science approaches to study chromatin
epigenomics and gene regulation. Current ongoing projects include:
multi-omics integration-based algorithm development for
transcriptional regulation prediction; model-based algorithm
development for single-cell epigenomics and spatial multi-omics
data analysis; statistical and computational modeling of
phase-separated transcriptional condensation; global epigenetic and
transcriptional regulation in T-cell immunity and various human
cancer systems, etc. More information on research directions and
previous publications can be found at the lab website:
The Zang Lab is well funded by NIH and other agencies. Each
postdoctoral scientist in the lab will receive comprehensive and
personalized training in research and career development, and will
have extensive opportunities for independent and collaborative
research. Based at the Center for Public Health Genomics in UVA's
School of Medicine, the lab has established close collaborations
with multiple labs both within and outside the university,
including departments of Biochemistry and Molecular Genetics,
Biomedical Engineering, Statistics, UVA Cancer Center and the new
founded School of Data Science, as well as several other
universities and research institutes.
Founded by Thomas Jefferson, University of Virginia is the first
public university and one of the most reputable research
universities in the United States. The university continues in its
mission to develop tomorrow's leaders who are well prepared to help
shape the future of the nation and the world.
1. To qualify for the positions, a Ph.D. or equivalent degree in
any quantitative science, including but not limited to
Bioinformatics, Computational Biology, Applied Mathematics,
Statistics, Physics, Chemistry, Computer Science, Data Science,
Engineering or a related field is required by start date;
2. Proficient in Python (or C/C++) & R programming;
3. Excellent communication and teamwork skills;
4. Strong quantitative background (e.g., statistical modeling,
machine learning, computational or theoretical physics, etc.) or
computational genomics experience (e.g., next-generation sequencing
5. At least one peer-reviewed publication written in English in
the previous area of research (not necessarily related to biology)
with submitted, accepted or published status at the time of
The University of Virginia is an equal opportunity and
affirmative action employer. Women, minorities, veterans and
persons with disabilities are strongly encouraged to apply.
All positions are restricted and contingent on the continuation
of funding. Please direct any questions or inquiries to
email@example.com. The positions will remain open until filled.
For further information regarding the application process,
please contact: Greg Haskins at firstname.lastname@example.org.
To apply please visit UVA job board
https://uva.wd1.myworkdayjobs.com/UVAJobs, and search for "
R0013309". Complete the application and see below for documents to
Required Application Materials:
* CV * Cover Letter * Contact information for 3 references
Please note multiple documents can be submitted in the CV/Resume
Box. Applications that do not contain all of the required documents
will not receive full consideration.
The selected candidate will be required to complete a background
check at time of offer per University Policy.
The University of Virginia, including 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