Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Germany
- Netherlands
- Norway
- Singapore
- Denmark
- France
- Australia
- Belgium
- United Arab Emirates
- Canada
- Switzerland
- Spain
- Sweden
- Italy
- Portugal
- Cyprus
- Finland
- Hong Kong
- Japan
- Luxembourg
- Morocco
- Poland
- China
- New Zealand
- Taiwan
- Bulgaria
- Estonia
- Ireland
- Malta
- Worldwide
- 22 more »
- « less
-
Program
-
Field
-
High-Energy Physics (HEP). We seek highly qualified candidates with interest and experience in ML algorithms including unsupervised techniques, time-series modeling, and clustering algorithms
-
? PhD position in Algorithms and Extremal Combinatorics There is a vacancy for a PhD Research Fellow in Algorithms and Extremal Combinatorics at the Department of Informatics . The position is for a fixed
-
projects involving methods development, novel algorithm development and/or in-depth data analysis that facilitates and integrates implementation, visualization, and database management of multi-dimensional
-
are poised to re-define our future mobility. However, full autonomy is not possible without all-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms
-
by emphasising AI systems that facilitate continuous interactions between humans and machine agents, potentially including multiple and embodied AI agents. Countering the current trends of very large
-
, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault diagnosis, and early fault prediction in electric vessels
-
optimization methods for implementation within the framework of the objectives of the doctoral thesis, starting with the exploration of methods based on genetic algorithms. Explore the possibilities
-
digital twins using prediction-powered inference to enhance reliability assessment; The theoretical analysis and algorithmic development of methods rooted in statistical learning theory, multiple hypothesis
-
research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
-
for real online scenarios and to study formal verification methods. The program will involve the study of machine learning tools and the development of simulation systems capable of integrating multiple data