Interested in pursuing a career as a statistician or data scientist at an academic institution? Perhaps you already have accepted an offer or will be on the market this coming year. Then you won’t want to miss this next career fair sponsored by NISS that will offer essential information about job opportunities for statisticians/data scientists in different academic environments. During this academic career fair, you will hear from senior statisticians and data scientists who will be on hand to provide attendees with an inside look at the varying aspects of research, teaching and service that statisticians in these academic institutions get involved in and the career opportunities available for you to consider!
So if you have received an offer for this fall, what advice would you like to have as you start your first year in the job? What should your priorities be – getting those publications sent out, perfecting your teaching, accepting service and committee assignments? How to answer these questions? We will ask several department heads, from different types of departments, to share their advice to their new hires.
Speakers:
Dr. Yehua Li Professor & Chair, Department of Statistics at University of California at Riverside (UCR)
Dr. Erin Schliep, Associate Professor, Department of Statistics at North Carolina State University (NCSU)
Dr. Petruța C Caragea - Professor & Associate Chair, Department of Statistics at Iowa State University (ISU)
Dr. Yan Ma, Professor & Chair, Department of Biostatistics, Orthopaedic Surgery, and Clinical and Translational Science at University of Pittsburgh (UPitt)
Moderator:
Dr. Piaomu Liu - Associate Professor, Department of Mathematical Sciences at Bentley University
Agenda
Each presenter will give a brief overview of their institutions and discuss their opportunities, then we will transition to a panel discussion that will address the following general topics:
- What advice do you give your new hires?
- How can a new hire seek colleague who can provide good career advice?
- What are the potential distinguishing characteristics of candidates for a tenure-track/tenured faculty position in your institution?
- What advice would you give to potential job candidates this coming year?
- What advice would you give about how Ph.D. students or postdocs should prepare for the future?
A live Q&A Session will take place after the panel discussion.
About the Speakers
Dr. Yehua Li is a Professor and the Department Chair of Statistics at University of California at Riverside. He got his Ph.D. in Statistics in 2006 from Texas A&M University. Before joining UCR in 2018, he held faculty positions in the University of Georgia and Iowa State University. He is a Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics, Elected Member of the International Statistical Institute, and a recipient of the National Science Foundation CAREER Award in 2012. He has served on the editorial boards of Canadian Journal of Statistics, Journal of Multivariate Analysis and Stat. His research interests include functional and longitudinal data analysis, non- and semi- parametric methods, spatial statistics, measurement error, mixture models, cardiovascular disease and neuroimage.
Dr. Erin Schliep is an Associate Professor of Statistics at North Carolina State University. She is currently serving as the search committee chair for this year's tenure-track assistant professor job opening. She completed her PhD at Colorado State University, was a postdoctoral fellow at Duke University, and spent seven years on the faculty at the University of Missouri before joining NCSU. She has research interests in Bayesian statistics, multivariate statistics, and spatiotemporal statistics. She has experience working on large collaborative research projects at the interface of statistics, environmental science, and ecology and has developed and maintained strong working relationships with researchers across disciplines, universities, and government agencies.
Dr. Petruța C Caragea - Professor Caragea joined the Department of Statistics at Iowa State University in 2003, after earning her M.S. and Ph.D. in Statistics from the University of North Carolina at Chapel Hill. Since 2014, she has served as the Department's Associate Chair and currently directs the Masters of Applied Statistics program, set to launch in fall 2025. She has chaired and served in numerous search committees at ISU, and plays an integral role in the graduate program, particularly in the recruitment and mentoring of graduate students. Her research focuses on developing statistical methodologies for data with spatial and temporal dependence, with applications in environmental, agricultural, and biological sciences. She actively collaborates with research teams at national laboratories, including NASA-JPL, PNNL, and LANL, as well as multidisciplinary groups at ISU.
Dr. Yan Ma is a Professor and Chair of the Department of Biostatistics and Health Data Science at the University of Pittsburgh. As a statistician, Ma has provided a wide range of traditional and cutting-edge statistical consulting services to biomedical and public health investigators and established very productive collaborations with them. His theoretical and computational statistical research interests include missing data imputation, machine learning, meta-analysis, methods for assessing interrater reliability, causal inference, complex sample surveys, and longitudinal methods. Through his collaborative research, Ma has become a statistician specializing in team science, translational science, and comparative effectiveness research. His areas of applications include orthopedics, anesthesiology, health disparities, cancer, HIV/AIDS, psychiatry, and emergency medicine. Ma was a recipient of Statistics in Epidemiology Young Investigator Award by ASA. Ma and his collaborators won the esteemed Team Science Award from the Association for Clinical Research Training, American Federation for Medical Research, Association for Patient Oriented Research, and Society for Clinical and Translational Science. This award recognizes the team's success in translation of research discoveries into clinical practice. Ma was selected to receive research fellowship from the Oak Ridge Institute for Science and Education (ORISE) Research Participation Program at the U.S. Food and Drug Administration. He was the winner of the Achievement in Academia Award for outstanding contributions to statistics and public health from the Applied Public Health Statistics Section of American Public Health Association. View Full Profile
About the Moderator
Piaomu Liu, Ph.D., is an Associate Professor in the Mathematical Sciences department at Bentley University. She earned her Ph.D. from the University of South Carolina, her M.S. from The University of Iowa, and her B.A. from Carleton College. With a strong academic background and a passion for teaching, Dr. Liu focuses on data science, applied multivariate statistics, and lifetime data analysis, helping students gain deep insights and practical skills in these critical areas.
In addition to her teaching responsibilities, Dr. Liu is actively engaged in several professional roles within the National Institute of Statistical Sciences (NISS). She serves as the chair of the NISS Graduate Student Network, sits on the NISS Affiliates Committee, and is a member of the NISS Academic Affiliates Subcommittee. Dr. Liu has also coordinated the NISS Writing Workshop, demonstrating her commitment to fostering academic growth and professional development among graduate students and peers.
Dr. Liu's research interests are centered around lifetime data analysis, including recurrent events and competing risks, joint dynamic modeling, and semiparametric methods. Her interdisciplinary research extends to various topics in data science, where she collaborates with other experts to address complex problems. Through her innovative research and dedication to teaching, Dr. Liu continues to make significant contributions to the field of mathematical sciences and to the academic community at Bentley University and beyond.
About the NISS Virtual Career Fair Series
This event is part of the NISS Virtual Career Fair Series: webinars where experienced statisticians from industry, government and academia talk about and provide advice for individuals interested in pursuing a career as a statistician. For more information about these events, please visit: https://www.niss.org/niss-affiliate-virtual-career-fairs
Event Type
- NISS Hosted