Sort by
Refine Your Search
-
Listed
-
Country
- United States
- United Kingdom
- France
- Sweden
- Germany
- Italy
- Belgium
- Spain
- Australia
- Netherlands
- Portugal
- Singapore
- Romania
- Canada
- China
- Denmark
- Finland
- Hong Kong
- Ireland
- Luxembourg
- Poland
- Andorra
- Austria
- Japan
- Macau
- Switzerland
- Barbados
- Czech
- Estonia
- Lithuania
- Malta
- Morocco
- Norway
- Saudi Arabia
- United Arab Emirates
- 25 more »
- « less
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Biology
- Economics
- Science
- Materials Science
- Business
- Mathematics
- Environment
- Chemistry
- Earth Sciences
- Law
- Linguistics
- Sports and Recreation
- Humanities
- Physics
- Psychology
- Arts and Literature
- Electrical Engineering
- Social Sciences
- Education
- 12 more »
- « less
-
Research Infrastructure? No Offer Description Mission: Support the design, training and validation of temporal models aimed at detecting ecological patterns and predicting events such as the bloom of Oceanic
-
optimisation by supplying high-quality data needed to validate and refine the next generation of predictive numerical models. A key innovation in this research will be the use of transparent soil analogues
-
or biases in data collection, storage, and processing pipelines. Additionally, the candidate will develop AI models that can adapt to dynamic and evolving data environments, incorporating mechanisms
-
impact-based health early warning systems. The successful candidate will join the research team of Dr. Joan Ballester Claramunt (https://www.joanballester.eu/ ) at ISGlobal within the framework
-
for Social Science, Modeling and Predicting, and introductory statistics courses. In order to meet Chinese visa requirements, prior to the position start date international (non-Chinese) candidates must have
-
on the integration of BIM, artificial intelligence and predictive maintenance (PM) for intelligent BIM models, digital construction sites, predictive analysis and immersive interactions, outlining an operating
-
application. The ambition of this research is to understand, and even predict through modeling, the damage process of tuffeau limestone in its most damaging form of deterioration: spalling. The hydromechanical
-
to the development of predictive enrollment and aid models using historical data and tools such as FAST and Rapid Insights, working in concert with the DSLE Executive Analyst. Serve as the DSLE liaison to Budget and
-
topics: a) introduction of highly efficient DGL models to reduce the energy impact and increase the sustainability of DGL models; b) increase the expressiveness of DGL models, obtaining better predictive
-
these models for scalable vision tasks, instance segmentation, tracking, classification, and more. You will utilize probabilistic models to produce uncertainty-aware predictions across scales. This role requires