Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Austria
- Germany
- France
- Netherlands
- Australia
- Belgium
- Norway
- Denmark
- Singapore
- Sweden
- China
- Luxembourg
- Spain
- Czech
- India
- Portugal
- Switzerland
- United Arab Emirates
- Canada
- Ireland
- Poland
- Hong Kong
- Italy
- Lithuania
- Romania
- Morocco
- New Zealand
- South Africa
- Andorra
- Armenia
- Barbados
- Croatia
- Cyprus
- Estonia
- Europe
- Finland
- Kyrgyzstan
- Latvia
- Slovenia
- Worldwide
- 32 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Biology
- Science
- Engineering
- Economics
- Mathematics
- Business
- Chemistry
- Environment
- Humanities
- Linguistics
- Arts and Literature
- Education
- Law
- Social Sciences
- Earth Sciences
- Philosophy
- Materials Science
- Electrical Engineering
- Psychology
- Physics
- Sports and Recreation
- Design
- 14 more »
- « less
-
of this PhD is to develop physics-informed neural operator frameworks that embed governing equations and invariants of fluid mechanics directly into learning architectures, enabling real-time, generalizable
-
such as Machine Learning, Natural Language Processing, AI in Education, Knowledge Representation, and Python-based analytical seminars at the BSc, MSc, and PhD levels. Responsibilities include assisting in
-
applications for faculty positions in Computer Science. Faculty specialising in data science, machine learning (deep learning, reinforcement learning, multimodal learning), Generative AI, and computer graphics
-
of almost 11,000 individuals, including approximately 7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. Fueled by curiosity and a deep sense
-
automated configuration mechanisms based on fingerprinting and machine learning to ensure traffic analysis remains faithful to the behavior of the monitored machines. Finally, you will validate your solutions
-
Pharmaceutical Roundtable. In this project we will employ deep learning-based protein sequence design tools to deliver biocatalysts for peptide synthesis. These designed enzymes will be further optimized using
-
comparing supervised and unsupervised methods (e.g., regularized regression, tree-based models, ensemble methods, clustering, dimensionality reduction) and deep learning approaches Developing and applying
-
vision, XR and generative models, specifically for capturing challenging scenarios and training deep learning systems to create better experiences for human users and learners. You will contribute
-
, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7
-
Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
Europe Research and Innovation Programme under the Grant Agreement No.101178775 Workplan: Design, develop and implement deep learning methodologies for generation of subsurface earth models. Duration