Research Associate, Department of Biomedical Engineering
About The Position
The Department of Biomedical Engineering at the University of Virginia seeks a highly motivated postdoctoral Research Associate to lead multidisciplinary systems biology projects in the laboratory of Dr. Sepideh Dolatshahi. The Dolatshahi Human Systems Immunology laboratory is active primarily at the interface of systems biology, immunology, and bioengineering. Research in the lab is built on our multidisciplinary experience in combining integrative computational immunology – data-driven, state-of-the-art single cell resolution and spatial methods, machine learning and kinetic modeling – with integrative experimental immunology to understand the fundamental mechanisms of immune regulation and dysregulation, with an ultimate objective of identifying strategies to improve immunotherapies and vaccines. The project will focus on studying immunology of pregnancy and immunity at the fetal-maternal interface. Research in the Dolatshahi lab benefits from proximity to the UVA hospital and active collaboration with leaders in Carter Immunology Center and the division of Fetal-Maternal Medicine at UVA. Candidates with strong background in molecular and cellular biology/immunology (or a related discipline) and interest in learning computational methods are particularly encouraged to apply. Candidates with bioengineering or systems biology background and extensive wet-lab experience are also strongly encouraged to apply. For more information visit Dolatshahi lab homepage at: https://www.dolatshahilab.com/. Postdoctoral employment is temporary and is normally limited to an individual who has been awarded a Ph.D. or equivalent doctorate within the previous five years and who will be involved in full-time research or scholarship at the University. Employment as a Postdoctoral Research Associate is viewed as training and is preparatory for a full-time academic or research career, is supervised by a senior scholar, and allows the appointee to publish the results of his/her research or scholarship during the training period. Candidates with strong background in molecular and cellular immunology (or a related discipline), molecular biology techniques, and interest in learning computational methods are particularly encouraged to apply. Candidates with bioengineering or systems biology background and wet-lab experience are also strongly encouraged to apply. The following qualifications are required: deep understanding of and coursework in molecular and cellular biology, immunology, and statistical and inferential analysis of data; strong oral and written communication skills with a strong publication record and grant report experience in relevant fields; proficiency in performing literature search/review; the capability to work effectively with graduate and undergraduate students, as well as colleagues from multiple disciplines; proficiency in computer programming such as MATLAB, R, or Python (this requirement could be changed from proficiency to familiarity if the suite of experimental skills are specifically strong and relevant; our lab can provide training to strengthen the computational proficiency). The following experience is preferred: broad biological knowledge in pregnancy and fetal-maternal medicine and immunity; experience with IRB-approved human cohort studies and placental tissue; the ability to gather, organize, and synthesize complex information to draw model assumptions and parameterization strategies for dynamic models; familiarity with variability across the human population as related to public health and social determinants of health; and familiarity with multiplex immunohistochemistry, spatial proteomics and transcriptomics.
Requirements
- deep understanding of and coursework in molecular and cellular biology
- deep understanding of and coursework in immunology
- deep understanding of and coursework in statistical and inferential analysis of data
- strong oral and written communication skills with a strong publication record and grant report experience in relevant fields
- proficiency in performing literature search/review
- the capability to work effectively with graduate and undergraduate students, as well as colleagues from multiple disciplines
- proficiency in computer programming such as MATLAB, R, or Python
Nice To Haves
- broad biological knowledge in pregnancy and fetal-maternal medicine and immunity
- experience with IRB-approved human cohort studies and placental tissue
- the ability to gather, organize, and synthesize complex information to draw model assumptions and parameterization strategies for dynamic models
- familiarity with variability across the human population as related to public health and social determinants of health
- familiarity with multiplex immunohistochemistry, spatial proteomics and transcriptomics
Benefits
- Learn more about UVA benefits.
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What This Job Offers
Job Type
Full-time
Education Level
Ph.D. or professional degree
Number of Employees
1-10 employees
