-
presentations. • Conduct comprehensive literature review and analysis of existing vibration data conversion methodologies, assessing their applicability to wooden packaging systems. • Develop practical design
-
interests are interdisciplinary modeling (ideally using economic production theory, more specifically Data Envelopment Analysis, system dynamics modeling/agent-based modeling, and/or Artificial Intelligence
-
techniques (e.g., SEM, XPS, ICP, XRD, TEM, or similar) evidenced by data collection or analysis in publications/reports. • Knowledge of corrosion science, demonstrated by coursework, thesis/dissertation
-
Forest Sector Industry: A Mixed-Methods Approach.” This interdisciplinary research initiative integrates stakeholder engagement, market analysis, and policy evaluation to develop a strategic
-
specialization in Data Science/Applied Econometrics and its application in applied economics and social sciences broadly defined. The position is one-year, 12-month, calendar-year appointment, with the possibility
-
Registry to advance recovery science. In addition, this position will work on secondary data analyses from clinical trials for opioid use disorder that are part of a funded project. Moreover, ARRC has
-
to hygrothermal or moisture diffusion processes. • Experience with experimental design, data collection, and analysis. • Ability to work both independently and collaboratively in an interdisciplinary research
-
several areas of ongoing research in the laboratory, including the isolation and genomic analysis of large DNA viruses, cultivation of diverse hosts, analysis of evolutionary relationships and genomic
-
, and with a strong background in numerical analysis and scientific computing. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility
-
modeling. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining. • Experience with analysis of time series data. • Solid