Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Sweden
- Netherlands
- Germany
- Spain
- Portugal
- France
- Singapore
- United Arab Emirates
- Norway
- Denmark
- Belgium
- Switzerland
- China
- Australia
- Austria
- Poland
- Italy
- Luxembourg
- Finland
- Canada
- Hong Kong
- Morocco
- Vietnam
- Ireland
- Romania
- Czech
- Japan
- Estonia
- Greece
- Brazil
- Saudi Arabia
- Croatia
- Lithuania
- South Africa
- Andorra
- Cyprus
- India
- Taiwan
- Malta
- New Zealand
- Slovenia
- Worldwide
- Israel
- Kenya
- Latvia
- 37 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Science
- Biology
- Business
- Mathematics
- Education
- Psychology
- Materials Science
- Earth Sciences
- Chemistry
- Arts and Literature
- Environment
- Social Sciences
- Humanities
- Linguistics
- Electrical Engineering
- Sports and Recreation
- Law
- Physics
- Philosophy
- Design
- Statistics
- 15 more »
- « less
-
component disciplines; in explainable multi-modal deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The researcher will conduct internationally-leading research in
-
inference, and Machine Learning methods. In addition to leading their own research projects, the appointed candidate will have the opportunity to contribute to the projects of PhD students in the group, as
-
automates building and modifying surface structures, submitting DFT calculations, post-processing electronic structure and vacancy energies, and extracting machine-learning descriptors for modeling oxygen
-
efficiency, and resource utilization. Strong expertise in machine learning, deep learning, and advanced time series modeling Additional education in economics (e.g., a completed Master’s or postgraduate degree
-
Science, Computer Science, Data Science, Neuroscience, or a related field by the start date. Demonstrated expertise in computational modeling of human behavior or computer vision / machine learning
-
contributions as a software engineer for a wide range of projects requiring computing systems design and realization, including machine learning (ML) and artificial intelligence (AI) applications including
-
for soft materials, with particular emphasis on thermo–visco–hyperelastic behavior, integrating continuum mechanics, scientific machine learning (SciML), and computational physics. The project aims
-
. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------------------------------------...
-
environmental factors such as fluctuating wind speeds and saltwater exposure. Using advanced statistical and machine learning techniques, including Bayesian inference and stochastic modelling, the project will
-
AI systems and interpretable machine learning, System integration implementation, Test environment configuration, Validation and stress testing, Deployment and configuration in test environments