Virginia Mountain View

Assistant Professor-Department of Biostatistics (F53040, F32430)

  • req6162
  • Richmond, Virginia, United States, 23284
  • Virginia Commonwealth University
Mission or Goal of Unit: The Department of Biostatistics is housed in the recently formed School of Public Health (SoPH) at Virginia Commonwealth University (VCU). With a 40+ year history within VCU’s Academic Health campus, the Department is committed to excellence, with a mission to improve human health through methodological research, graduate education, and collaboration with health science researchers on biostatistical methods and applications. Majority of our biostatistics faculty, students, and staff collaborate with clinical investigators on the VCU Academic Health campus (which includes the Schools of Medicine, Dentistry, Pharmacy, Nursing, the College of Health Professions, the Massey Comprehensive Cancer Center) in a wide variety of complicated, hierarchical, and multifaceted health problems. As educators, we aim to train the next generation of biostatisticians, bioinformaticians, and data scientists in methodological, collaborative, and leadership skills by offering both M.S. and Ph.D. programs in Biostatistics, including a concentration in Genomic Biostatistics, and a M.S. in Clinical Research in Biostatistics. The department is committed to fostering a diverse, equitable, and inclusive environment. For more details, please visit https://biostatistics.vcu.edu/

Located in the heart of Richmond, Virginia, VCU is a premier urban, public research university, committed to student success and community service. One of just a handful of universities to receive both a "Very High Research Activity (R1 status)", and a "Community Engaged" designation from the Carnegie Foundation, VCU also boasts nine programs in the U.S. News and World Report's top 10, as well as the region's top-rated medical center. Richmond's lively and welcoming city provides the ideal backdrop for VCU's academic work. Rich in culture and history, the city becomes a living laboratory where our faculty, staff, and students can tackle problems directly affecting our local communities and see the impact of their work first-hand.

Chief Purpose of this position: The Department of Biostatistics at Virginia Commonwealth University invites applications for two, full-time, 12-month, tenure-track faculty positions at the rank of Assistant Professor. One position will focus on candidates with expertise in methodology development and applications of AI/ML (such as, deep learning, transfer learning, large language models, generative AI, etc) and other Data Science techniques, leading to a state-of-the-art predictive modeling in biomedicine. The candidate is expected to have significant computational knowledge in Python, C++, GPU programming, and in other relevant AI/ML platforms, and thus contribute to the teaching and research mission of the department. The other position will seek candidates with broad research expertise; in particular, candidates with specific expertise in topics that include, but are not limited to, spatial and spatio-temporal methodology, causal inference, handling and analyzing electronic health records and national survey data, dynamic treatment regime and precision medicine, functional data, advanced Bayesian methods, and big data are encouraged to apply. The Department is one of the highest funded entities within the newly formed SoPH, thus offering remarkable opportunities towards the growth of the research trajectory. The faculty members are expected to foster the tripartite mission (excellence in teaching, research and service) of the department by successfully competing for independent and collaborative extramural funding, developing their own program of research, and contributing to the teaching mission of the department.

Position Responsibilities:

Teaching: The faculty member will share a deep commitment to effective instruction, creation of innovative courses, and mentoring students in research, outreach, and professional development related to the Biostatistics graduate programs. In addition to teaching courses that align with their research expertise, they are also expected to teach basic (and sometimes, introductory level) graduate biostatistics courses. The usual teaching load is 2 courses per year (1 each semester), but it is also dependent on the percentage of generated extramural support.

Research: The faculty members are expected to generate solid methodological publications, and thus develop their own research program leading to principal-investigator initiated extramural funding. They are also heavily encouraged to engage in collaborations with investigators within various Schools and Colleges of the VCU Academic Health campus, as well as across the university, publish, and seek extramural funding.

Service: The faculty members are expected to serve on Departmental, School, and/or University committees as necessary, as well as in a professional capacity in their discipline of interest (e.g., reviewer, conference organizer, etc.)

Required Qualifications:
  • Ph.D. or equivalent terminal degree in Biostatistics, Statistics, Bioinformatics, Computer science, or a closely related field
  • Proven publication record in the area of biostatistics, statistics, and/or computer science
  • Ability to work independently
  • Proficiency in statistical software, such as Python, R, SAS, or STATA
  • Ability to establish their own program of research developing novel methodologies
  • Strong collaborative skills and ability to conduct complex statistical analysis
  • Demonstrated experience working in and fostering a diverse faculty, staff, and student environment, or commitment to do so as a faculty member at VCU

Preferred Qualifications:
  • Postdoctoral research training experience
  • Experience in trainee mentorship
  • Teaching experience at the graduate or undergraduate level
  • Experience developing grant proposals.

ORP Eligible: Yes

 

Each agency within the Commonwealth of Virginia is dedicated to recruiting, supporting, and maintaining a competent and diverse work force. Equal Opportunity Employer

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