A new position for a postdoctoral associate is available in the Virginia Tech Department of Statistics (www.stat.vt.edu), with Professor Robert B. Gramacy (bobby.gramacy.com) and with colleagues at the Virginia Tech Center for Ecosystem Forecasting (www.ecoforecastprojectvt.org). VT Stats is at the forefront of research and teaching in Uncertainty Quantification and applications of dynamic and stochastic modeling and data-centric inference in the physical and engineering sciences.
The Center for Ecosystem Forecasting is a vibrant, highly collaborative, interdisciplinary research center developing real-time ecological forecasting models, software, and computing infrastructure to inform day-to-day environmental resource management. This NSF-funded position will provide the postdoctoral researcher the opportunity to lead publications on the frontier of methodology for surrogate modeling of high-powered computer models of complex natural and biological systems, their interface with environmental data products and forecasts, and their calibration to sensor measurements towards the development of a real-time platform for the management of natural resources (https://news.vt.edu/articles/2023/08/flsi-nsf-grant-cayelan-carey.html).
Research activities will include: upgrading the surrogate modeling toolkit to accommodate massive stochastic simulation campaigns, input-dependent noise (heteroskedasticity), non-stationary dynamics, and the synthesis of simulation and field observations, all while interfacing with other team members who are developing the simulation models, managing the sensors and recording the field data, and developing a real-time monitoring/forecasting platform for managers.
The position is in-person, based on-campus at Virginia Tech (Blacksburg, VA, USA). The position start date will be flexible, aiming for Summer 2024. Funding is available for up to two years, contingent upon successful annual reviews.
- A Ph.D. in statistics, machine learning, or a related field. PhD awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
- Experience in publishing peer-reviewed journal articles in statistics or machine learning
- Experience working in the R programming language
- Experience with collaborative coding projects and using version-control tools (e.g., Git)
- Interest in working in interdisciplinary, collaborative teams
- Significant research experience in surrogate modeling/emulation of computer simulation experiments or Gaussian Process regression.
- Experience working in a Unix environment (e.g., bash shell and shell scripting)
- Experience with compiled languages (i.e., C/C++) and their interface with high-level
- Experience with distributed computation (e.g., OpenMP, MPI, GNU Parallel)
- Experience with public release of packaged open source software (e.g., on CRAN)
- Demonstrated ability to work in interdisciplinary, collaborative teams
Commensurate with experience
March 15, 2024
The successful candidate will be required to have a criminal conviction check.
About Virginia Tech
Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.
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