[Please Note: This session has already occurred. Go to the News Story to read about what happened.]
Interested in pursuing a career as a statistician at an academic institution? 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.
This event is the first NISS Career Fair for the Fall of 2021 - several more are in the planning phases! Keep your eye on the list of upcoming events on the NISS website or subscribe to the NISS Newsletter.
This session features opportunities for statisticians/data scientists from three NISS Affiliate academic departments. Department Chairs from Penn State University's Department of Statistics, Columbia University's Department of Statistics and the University of South Carolina's Department of Statistics 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! All three institutions are currently looking to fill multiple positions!
This session will be moderated by Irina Gaynanova (Texas A&M University).
Each presenter will have 20 minutes to address the following general topics:
- What are the preferred qualifications for a tenure-track/tenured faculty position in your institution?
- What are the potential distinguishing characteristics of candidates for a tenure-track/tenured faculty position in your institution?
- What advice would you give to job candidates?
- What advice would you give about how Ph.D. students or postdocs should prepare for the future?
Previous Virtual Career Fairs
The following Career Fairs have taken place in previous years. Follow the link to review the advice from senior statisticians in a wide array of sectors!
March 11, 2020 "Career Paths Highlighted in Three Health Related Government Agencies"
February 19, 2020 "Advice and Insights Offered During Third NISS Industry Career Fair"
January 8, 2020 -"NISS Government Career Fair Outlines Opportunities for Statisticians!"
December 6, 2019 - "Opportunities in Banking & Marketing Sectors Highlighted in Virtual Career Fair"
September 26, 2019 - "NISS Virtual Career Fair for NISS Affiliates"
The Career Fair will be conducted using Zoom.
The program for this virtual career fair will be organized as follows:
12:00-12:05 Opening remarks by the Moderator, Irina Gaynanova (Associate Professor of Statistics, Texas A&M University)
12:05-12:25 Murali Haran, (Professor and Department Head, Department of Statistics at Penn State University)
12:25-12:45 Tian Zheng, (Professor and Department Head, Department of Statistics at Columbia University), and
12:45-1:05 Joshua Tebbs, (Professor and Department Head, Department of Statistics at University of South Carolina)
About the Speakers
Murali Haran is Professor and Department Head of Statistics at Penn State. He received his Ph.D. and M.S. in Statistics from the University of Minnesota, and his B.S. in Computer Science from Carnegie Mellon University. His research is in the areas of statistical computing, primarily Markov chain Monte Carlo algorithms. He also works on spatial models, particularly latent Gaussian random fields, complex computer models ("computer experiments"), and statistical emulation and calibration. Much of his research is heavily motivated by cross-disciplinary research in climate science and infectious diseases. He served co-editor of Bayesian Analysis from 2016 to 2018, and has served as associate editor for a number of journals, including Technometrics, The American Statistician, Journal of Agricultural, Biological and Environmental Statistics, Biometrics and Bayesian Analysis. From 2013-2014 he was Chair of the American Statistical Association (ASA) Section on Risk Analysis, and was the treasurer for the International Society for Bayesian Analysis (ISBA) from 2014 to 2016. At Penn State, he served as Chair of the Penn State Statistics Undergraduate Program from 2012 to 2016. He has been part of several climate science-related organizations/initiatives, including NSF-sponsored SCRiM (Sustainable Climate Risk Management), a multi-institution network with Penn State as the hub. He was the director of the Penn State Node of the NSF research network STATMOS, and a member of the ASA Advisory Committee on Climate Change Policy (2009 - 2014).
Tian Zheng is Professor and Department Chair of Statistics at Columbia University. She obtained her PhD from Columbia in 2002. She develops novel methods for exploring and understanding patterns in complex data from different application domains such as biology, psychology, climatology, and etc. Her current projects are in the fields of statistical machine learning, spatiotemporal modeling and social network analysis. Professor Zheng’s research has been recognized by the 2008 Outstanding Statistical Application Award from the American Statistical Association (ASA), the Mitchell Prize from ISBA and a Google research award. She became a Fellow of American Statistical Association in 2014. Professor Zheng is the receipt of 2017 Columbia’s Presidential Award for Outstanding Teaching. In 2018, she will be the chair-elect for ASA’s section on Statistical Learning and Data Science. Professor Zheng was an associate editor for Journal of American Statistical Association – Applications and Case Studies from 2007 to 2013 and a current AE for Statistical analysis and data mining (SAM) and Statistics in Biosciences (SIBS), also a Faculty member of F1000 Prime. She is on the advisory board for STATS at Sense About Science America that targets to develop a statistical literate citizenry.
Joshua Tebbs is Professor and Chair in the Department of Statistics at University of South Carolina. He obtained his BS in Mathematics and MS in Statistics from University of Iowa and his PhD in Statistics from North Carolina State University. His primary research interests are in the development of statistical methods for categorical data, especially aggregated or group tested data and their application in infectious disease screening, as well as in general biostatistical methods and problems involving ordering or shape restrictions. He is an elected member of the International Statistical Institute, a fellow of the American Statistical Association, and his research program is funded by the National Institutes of Health (NIH). He is currently Editor-in-Chief at American Statistician, Associate Editor at Statistics in Medicine, and a member of the Biostatistical Methods and Research Design (BMRD) Study Section of the NIH.