Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Sweden
- United Kingdom
- Netherlands
- Norway
- Germany
- Australia
- Belgium
- France
- Denmark
- Singapore
- Spain
- Luxembourg
- Switzerland
- Finland
- Canada
- Ireland
- Italy
- Portugal
- Hong Kong
- Austria
- China
- United Arab Emirates
- Estonia
- Morocco
- Cyprus
- Czech
- Romania
- Japan
- Lithuania
- Poland
- Saudi Arabia
- India
- Macau
- Vietnam
- Andorra
- Armenia
- Kyrgyzstan
- Malta
- Worldwide
- 30 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Economics
- Medical Sciences
- Biology
- Science
- Business
- Mathematics
- Materials Science
- Chemistry
- Environment
- Arts and Literature
- Education
- Psychology
- Earth Sciences
- Electrical Engineering
- Social Sciences
- Linguistics
- Humanities
- Philosophy
- Law
- Sports and Recreation
- Design
- Physics
- 14 more »
- « less
-
the Research Grant Regulations of the Foundation for Science and Technology. 6. Work plan: The RiskMap project aims to develop an AI-driven tool to map degradation risks on historic building facades, using
-
About the Opportunity Job Summary The Snowflake Developer is responsible for designing, developing, optimizing, and operationalizing Northeastern University’s Snowflake data platform. This role
-
engineering Machine learning or AI methods (e.g. anomaly detection, classification, regression, time-series modelling) Programming skills (e.g. Python, MATLAB or similar) Experience with industrial systems
-
qualifications (required at time of application) Doctoral degree in engineering, oceanography or a related field, with relevant background in data-driven modeling, machine learning and/or fluid mechanics
-
of the future, including: the use of faster processors being pushed by CubeSat technology; new requirements for cybers ecurity driven by actual threats; ever-higher data streams and volumes downlinked from
-
-fidelity finite-element model structural analyses. The motivation is driven by the desire of the Portuguese leading UAS manufacturer to greatly automate the meshing process, within its in-house UAV design
-
rupture, which is one cause of a stroke and thus the prediction of plaque rupture is very relevant. The steps in the development of surrogate models are building data-driven models from medical imaging
-
emerging areas of science and technology. (For more details, please visit https://www.fst.um.edu.mo/ and https://fhs.um.edu.mo/en/#/ ). The Department of Biological Science strives to excel in both
-
to: Develop mechanistic and data-driven models to analyse concentration–response relationships and biological readouts from advanced in vitro assays Apply statistical and computational methods to quantify
-
recently seen the first results in application to engineering materials for wear and plastic damage in steel. A significant opportunity is FLAME GPU general-purpose modelling framework developed in Sheffield