Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- France
- Portugal
- Germany
- Sweden
- Netherlands
- Norway
- Spain
- Belgium
- Denmark
- Italy
- Singapore
- Australia
- Finland
- Morocco
- Ireland
- Luxembourg
- Switzerland
- China
- Canada
- Poland
- Czech
- Austria
- Japan
- Estonia
- Hong Kong
- Brazil
- United Arab Emirates
- Vietnam
- Andorra
- Macau
- Malta
- Saudi Arabia
- Slovakia
- Barbados
- Bulgaria
- Iceland
- Latvia
- Slovenia
- 30 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Biology
- Economics
- Science
- Materials Science
- Mathematics
- Earth Sciences
- Chemistry
- Business
- Environment
- Humanities
- Arts and Literature
- Psychology
- Law
- Linguistics
- Physics
- Social Sciences
- Electrical Engineering
- Sports and Recreation
- Education
- Design
- Philosophy
- 14 more »
- « less
-
learning (AI/ML) being a major focus. Many of the laboratory's interests center around the identification of small molecules using mass spectrometry data, and the use of language models to predict
-
. 3. Machine Learning and Predictive Analytics: • Develop and apply machine learning models (including Azure Machine Learning) to optimize healthcare data analysis accuracy. • Collaborate with data
-
predictive analytics. Identifies and investigates significant differences or anomalies in data. Uses appropriate quantitative and qualitative analysis to analyze survey data. Conducts longitudinal analysis and
-
field. This approach is related to data assimilation, allowing for better prediction, control, and optimisation of turbulent systems in engineering, energy, and environmental applications
-
application! Your work assignments Spatio-temporal processes are everywhere in science and engineering, with applications ranging from weather prediction to cardiovascular medicine. Developing machine learning
-
will build an experimental and computational platform based on 3D-printed, brain-mimetic tissue models with tunable transport properties, where interface transport can be measured and predicted
-
, inspection histories, operational performance data, hyperspectral imagery, train-borne video analytics and satellite soil-moisture products to build predictive models of vegetation-driven and water-driven
-
regarding the reliability and translational value of in vitro models for predicting carotenoid bioaccessibility across diverse food matrices. The findings will have important implications for nutrition
-
of existing studies to promote the use of risk-informed decision frameworks, prediction models, AI applied to planetary protection. Tasks include: Support the creation of probabilistic models for planetary
-
mining challenges. The overarching objective of this project is to develop computational models that can predict how effectively glycine-based solutions extract precious metals from ore, enabling