Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); yesterday published
- University of Sheffield
- CNRS
- Delft University of Technology (TU Delft); Delft
- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Delft University of Technology (TU Delft); today published
- European Space Agency
- Fraunhofer-Gesellschaft
- IMEC
- ISCTE - Instituto Universitário de Lisboa
- Lulea University of Technology
- Northeastern University
- Tallinn University of Technology
- University of Glasgow
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Blekinge Institute of Technology
- Cranfield University
- Delft University of Technology (TU Delft); 16 Oct ’25 published
- Florida Atlantic University
- Forschungszentrum Jülich
- Heraeus Covantics
- INESC TEC
- King Abdullah University of Science and Technology
- Linköping University
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- McGill University
- NIST
- Nature Careers
- Northern Alberta Institute of Technology
- Tampere University
- Technical University of Denmark
- Technical University of Munich
- Texas A&M AgriLife
- Texas A&M University System
- The Ohio State University
- Umeå University
- Universidad de Alicante
- Universidade do Minho - ISISE
- University of Central Florida
- University of Delaware
- University of East Anglia
- University of Essex;
- University of Groningen
- University of Liège
- University of Nevada, Reno
- University of North Carolina at Chapel Hill
- University of Oulu
- University of Southern Denmark
- Université Savoie Mont Blanc
- Université Toulouse III Paul Sabatier
- Uppsala universitet
- VTT
- Vrije Universiteit Brussel
- Zintellect
- 45 more »
- « less
-
Field
-
selectivity is the first important barrier to overcome in order to perform quantitative analyses for each pollutant and avoid ionic interference between the different sensors used in the project. Sensor
-
across different imaging devices, including future sensors with unknown spectral sensitivities. Training The student will be based at the Colour & Imaging Lab at the School of Computing Sciences which has
-
, integrate, and validate sensors, especially but not limited to biomedical sensors for physiological monitoring. --Collect experimental data, implement algorithms and signal processing, contribute to system
-
) Development of methods and algorithms to create and update digital maps in forest environment; 2) Development of SLAM algorithm and map representation that facilitates the use of different sensors and sensor
-
to track how the prevalences of different strains in a mixed sample change over time. Your role: You will develop and implement algorithms to find, quantify and track mutations in evolving populations
-
. Neuromorphic fusion of co-localized visual sensors Fusing different sensory modalities is a powerful mechanism to extract information about a perceived environment: throughout our lives, we hear with our eyes
-
algorithms for multi-sensor fusion for autonomous navigation in harsh environments. You must be able to express yourself both orally and in writing in English as it is part of the task of communicating
-
. For example, we would like to be able to track how the prevalences of different strains in a mixed sample change over time. Your role: You will develop and implement algorithms to find, quantify and track
-
algorithm-driven sensing systems, remote sensing and multi-modal sensor integration Applicants do not need to cover all areas listed above but should bring strong expertise in at least one and a broad
-
measurement capabilities, in many cases surpassing what is currently achievable from suborbital platforms. Importantly, each mission employs different measurement techniques, applied at varying resolutions and