Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- Rutgers University
- Case Western Reserve University
- Florida International University
- Nature Careers
- Northeastern University
- Purdue University
- Stony Brook University
- The Ohio State University
- University of California
- University of California, San Diego
- University of Houston Central Campus
- University of South Carolina
- University of Washington
- 3 more »
- « less
-
Field
-
to facilitate the accomplishment of biodiversity conservation research objectives. Develops and writes new proposals to secure contracts for grant-funded research related to biodiversity conservation and the use
-
tenured/tenure-track faculty and nine full-time instructors. Current research areas of the faculty include survival and reliability analysis, Bayesian statistics, latent variable methods, item response
-
with large datasets, with a minimum 200 records, using statistical software packages including SAS, R, SPSS, and STATA. (Required) Demonstrated knowledge of at minimum one general object-oriented
-
integrate sophisticated AI systems, rigorously testing, validating, and tracking learning models, and troubleshooting issues to ensure system accuracy and reliability. A core objective of this role is to
-
techniques. The incumbent is expected to exercise sound judgment in selecting and applying appropriate methods and techniques to achieve research objectives, working independently within broadly defined
-
and advanced quantitative techniques¿including fluorescence correlation spectroscopy, single¿particle tracking, time¿resolved anisotropy, cryo¿EM particle¿counting, and Bayesian fitting¿to extract
-
of Business at The Ohio State University invites applications for a tenure-track faculty position (open rank) in the Department of Marketing and Logistics. We seek candidates with expertise in quantitative
-
areas including the Global Burden of Diseases (GBD), Injuries, and Risk Factors; Future Health Scenarios; Cost Effectiveness and Efficiency; Resource Tracking; and Impact Evaluations. IHME is committed
-
a spatially explicit predictive model for Everglades vegetation dynamics in response to major drivers. The major objectives are to explore the distribution models that discriminate among prairie and
-
computational modeling, geometric morphometrics, multivariate and Bayesian statistics, spatiotemporal and spatial modeling (including GIS), causal inference, machine learning, AI, and statistical software