Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Netherlands
- Germany
- Sweden
- Norway
- Denmark
- France
- Spain
- Portugal
- Australia
- Belgium
- Finland
- United Arab Emirates
- Switzerland
- Canada
- China
- Singapore
- Greece
- Italy
- Estonia
- Hong Kong
- Morocco
- Poland
- India
- Luxembourg
- New Zealand
- Austria
- Cyprus
- Czech
- Malta
- Romania
- Saudi Arabia
- 23 more »
- « less
-
Program
-
Field
-
a focus on creating an inclusive and bottom-up driven research environment. Our workplace consists of a diverse set of people from different nationalities, backgrounds and fields. As a PhD student
-
. It is not feasible to scan the full volume of such samples at the highest desired resolution. Therefore, we require an imaging scheme that acquires relevant features at different length scales and
-
research environment. Our workplace consists of a diverse set of people from different nationalities, backgrounds and fields. As a postdoctoral researcher working with us, you receive the benefits
-
manner, and (2) design AI approaches such as learning algorithms and reasoning engines that can exploit the provided knowledge? The successful candidate will conduct research on how to build software
-
mechanisms are essential for effective energy collaboration. These coordination mechanisms we call ‘energy hub control centers’ and they may differ from traditional control rooms, accommodating both
-
of novel satellite data analysis algorithms and solutions that will form the technology foundation for new products. The position is for a period of three years. Admission to the PhD programme is a
-
manipulators capable of adjusting their trajectory and resistance in real time in response to variable external loads. This module should integrate learning algorithms based on artificial intelligence, allowing
-
Offer Description The researcher will develop various applications, algorithms, and AI techniques for Virtual Power Plants (VPPs) within the distribution grid environment. These will include neural
-
in mathematical theory. Unlike standard deep networks, each connection in a KAN learns a continuous function, allowing a richer and more flexible representation of computation. This perspective aligns
-
learning models (semantic segmentation, domain adaptation, multimodal AI) to analyze plant and environmental data. Support the integration of AI algorithms with robotic and sensing systems for real-world