Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Delft University of Technology (TU Delft)
- Cranfield University
- University of Exeter
- Linköping University
- Forschungszentrum Jülich
- Newcastle University
- Technical University of Denmark
- UiT The Arctic University of Norway
- University of Bergen
- Aalborg Universitet
- Aalborg University
- CNRS
- Cranfield University;
- DTU Electro
- Eindhoven University of Technology (TU/e)
- Inria, the French national research institute for the digital sciences
- Institute of Biochemistry and Biophysics Polish Academy of Sciences
- KU LEUVEN
- Loughborough University;
- Manchester Metropolitan University
- Oak Ridge National Laboratory
- Tallinn University of Technology
- Technical University Of Denmark
- Technical University of Munich
- Universidade de Vigo
- University College Dublin
- University of Adelaide
- University of Birmingham
- University of Bremen •
- University of Cambridge
- University of Surrey
- University of Surrey;
- Université Toulouse Capitole
- 23 more »
- « less
-
Field
-
, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
-
series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is
-
uncertainties. Determining how to account for these uncertainties leads to research questions spanning from data collection and estimation to model representations and optimization algorithms. In the field
-
some of the following skills: Localization and sensor fusion: Solid understanding of localization techniques and sensor integration. Experience with SLAM algorithms (vision-, acoustic-, or inertial-based
-
sensor integration. Experience with SLAM algorithms (vision-, acoustic-, or inertial-based), state estimation (e.g. Kalman filtering, pose graph optimization), or collaborative positioning is highly valued
-
the number of sensors required and the maintenance of the data acquisition system. Hence, the alternative of direct instrumentation of the structure, whilst effective, can be logistically expensive
-
Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 5 days ago
The spectacular development of space systems and sensors, for observing the Earth and other Planets, provides access to numerous geophysical, geochemical and biophysical parameters over vast areas with increasingly
-
Project advert Modern artificial intelligence (AI) increasingly relies on combining multiple sources of information, such as sound, motion, images, and sensor data, to achieve robust and intelligent
-
in the live organism to study e.g. immune responses or cancer development. Moreover, using molecular sensors we also aim to read out cellular functionality in vivo e.g. metabolic reprogramming in
-
depletion, toxic algae, and pollutants. This natural sensitivity makes them powerful bio-sensors for environmental monitoring, capable of providing early warnings of ecosystem stress. However, harnessing this