Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- France
- Portugal
- Germany
- Sweden
- Netherlands
- Spain
- Norway
- Belgium
- Denmark
- Italy
- Singapore
- Australia
- Finland
- Ireland
- Switzerland
- Luxembourg
- China
- Czech
- Canada
- Morocco
- Austria
- Estonia
- Poland
- Japan
- Hong Kong
- United Arab Emirates
- Brazil
- Malta
- Vietnam
- Andorra
- Macau
- Saudi Arabia
- Barbados
- Bulgaria
- Iceland
- Latvia
- Romania
- Slovenia
- 30 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Biology
- Economics
- Science
- Materials Science
- Mathematics
- Earth Sciences
- Chemistry
- Environment
- Business
- Humanities
- Arts and Literature
- Linguistics
- Psychology
- Law
- Physics
- Electrical Engineering
- Social Sciences
- Sports and Recreation
- Education
- Design
- Philosophy
- 14 more »
- « less
-
) for seismic data prediction. The use of neural networks to predict seismic velocity models has shown increasingly accurate and efficient results. The proposed technique will incorporate region-specific
-
the most active pre-main-sequence end of the cool star sequence, where the stellar environment is most extreme and the atmospheric consequences most dramatic, we build towards a unified predictive model
-
next-generation machine learning (ML) models that are both data-efficient and transferable, enabling more reliable catastrophic risk prediction, defined as the probability of exceeding critical safety
-
experimentally, followed by further model improvements, and implementation or design of a robust workflow and predictive design tool. Where to apply Website https://www.academictransfer.com/en/jobs/359149/engd
-
, nuclear waste), (ii) predict its behaviour for accidental contaminations, and (iii) offer relevant solutions of remediation. Reliable tools to model the transport of the interested fluids are therefore
-
to identify those most at risk from extreme heat, as well as offering personalized adaptation advice --- translating rich multi-modal data into interpretable, scalable prediction and advising models. ICARUS
-
. Your Role A key pillar of ECOWIND is bridging the gap between remote sensing technology and real-time turbine control. Your focus will be the development of a predictive capability that allows turbines
-
teams. Unit URL https://imci.uidaho.edu/ Position Qualifications Required Experience Experience with statistical or predictive modeling as demonstrated by publications in the field Evidence of strong
-
to replicate floating wind turbine farms, with particular attention to the aerodynamic modeling of individual turbines and wake modeling. The objective of this activity is to assess the effects of interactions
-
produced under conditions representative of rocket engines, for a selection of metals. After meticulous experimental characterization, the unique database obtained will be exploited to enhance the modeling