Biostatistics Postdoctoral Research Associate, Public Health Sciences

The Biostatistics Division in the Department of Public Health Sciences in the School of Medicine at the University of Virginia (UVA) invites applications for a highly motivated Postdoctoral Research Associate. This position offers an excellent opportunity to work alongside Dr. Hong Zhu and a multidisciplinary research team, contributing to innovative methods in comparative effectiveness research using complex observational healthcare data, with a focus on cancer studies.

The successful candidate will be expected to:

• Modeling multilevel survival data while addressing confounding and missing data issues.
  
• Utilizing machine learning techniques as appropriate for data analysis.
  
• Developing computing programs and software to support research initiatives.
  
• Applying new methodologies to real-world healthcare data.
  
• Actively contributing to the preparation of publications for peer-reviewed journals.
  
• Assisting in the preparation of grant proposals for funding agencies.
  

This role is ideal for a candidate seeking hands-on experience in biostatistical research within a dynamic academic environment and aiming to make impactful contributions to the field.

For additional information about the position, please contact Hong Zhu, Professor , at hzhu2m@virginia.edu.

Minimum Requirements:

Doctoral degree

Preferred Qualifications:

• PhD in biostatistics, statistics, or a related quantitative field by the appointment start date.
  
• Strong background and experience in, survival analysis, missing data methods, causal inference, machine learning
  
• Proficiency in R and SAS/STATA.
  
• Excellent written and verbal communication skills.
  

This is a 12-month appointment with the possibility of renewal contingent upon satisfactory performance and the availability of funding. Salary is commensurate with education and experience.

This is a restricted position; continuation is dependent on funding and satisfactory performance.

This position will sponsor applicants for work visa who meet the qualifications.

This position will remain open until filled. The University will perform background checks on all new hires prior to employment. A completed pre-employment health screen is required for this position prior to employment.

This is an Exempt level, benefited position. For more information on the benefits at UVA, visit hr.virginia.edu/benefits

To Apply:

Please apply through Careers at UVA , and search for R0066529 .

Internal applicants must apply through their UVA Workday profile by searching 'Find Jobs'.

Complete an application online with the following required documents:

• 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.

For additional information regarding the application process, please contact Yelena Markazyan, Academic Recruiter at ym3mm@virginia.edu

For more information about UVA and the Charlottesville community please see http://www.virginia.edu/life/charlottesville and https://embarkcva.com/ .

For more information on the benefits available to postdoctoral associates at UVA, visit postdoc.virginia.edu and hr.virginia.edu/benefits .

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 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, pregnancy, sexual orientation, veteran or military status, and family medical or genetic information.