Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- France
- Germany
- United Kingdom
- United Arab Emirates
- Netherlands
- Norway
- Spain
- Portugal
- Austria
- Belgium
- Italy
- Singapore
- Sweden
- Poland
- Australia
- Denmark
- Switzerland
- Canada
- China
- Japan
- Estonia
- Finland
- Hong Kong
- Ireland
- Luxembourg
- Mexico
- Brazil
- Czech
- Iceland
- New Zealand
- Romania
- Slovenia
- Vietnam
- 24 more »
- « less
-
Program
-
Field
- Computer Science
- Economics
- Medical Sciences
- Engineering
- Biology
- Science
- Mathematics
- Earth Sciences
- Materials Science
- Chemistry
- Business
- Environment
- Education
- Physics
- Social Sciences
- Psychology
- Electrical Engineering
- Humanities
- Arts and Literature
- Law
- Philosophy
- Linguistics
- Sports and Recreation
- 13 more »
- « less
-
materials and structures. By combining numerical modeling, laboratory experiments, and theoretical analyses, we seek to link microscopic processes with the macroscopic behavior of both engineering and natural
-
forward models and inverse-scattering approaches for reflection-mode electron imaging, using simulations and experimental reconstructions to understand the capabilities and limitations of the technique. As
-
new analytical methods and numerical models, designing and executing laboratory and field experiments, integrating observational data with theoretical and computational approaches, and evaluating
-
will investigate how realistic propagation conditions and hardware imperfections affect resilience and how simulation and experimental models can be reconciled. The expected outcome is a set of
-
College of Education, Health and Human Sciences. The CDHD is supported through a federal infrastructure grant with numerous projects funded through sponsored accounts. The CDHD improves the lives of people
-
scientific and engineering disciplines, including ground-based, airborne and satellite measurements, as well as numerical modeling and data analysis of various climate parameters. The division operates ground
-
analysis (FEA) and numerical modelling, preferably using Abaqus. Good programming skills, preferably in Python. Ability to work effectively both independently and as part of a multidisciplinary research team
-
preparation, mesh generation, solver execution, and post-processing. Validate CFD predictions against experimental wind-tunnel measurements and establish best-practice guidelines for turbulence modelling and
-
influenced today’s widely used AI products. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Postdoctoral Fellow to lead research on AI training algorithms. The role will focus
-
) composites, with experience in testing, manufacturing, or modeling preferred. Working within a collaborative team of PhD-level scientists and undergraduate student, the successful candidate will conduct