Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Cranfield University
- Delft University of Technology (TU Delft)
- Fraunhofer-Gesellschaft
- Tallinn University of Technology
- CNRS
- Forschungszentrum Jülich
- University of Exeter
- Uppsala universitet
- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Delft University of Technology (TU Delft); yesterday published
- ISCTE - Instituto Universitário de Lisboa
- National University of Science and Technology POLITEHNICA Bucharest
- Newcastle University
- Technical University of Denmark
- UiT The Arctic University of Norway
- University of A Coruña
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Cranfield University;
- DTU Electro
- Delft University of Technology (TU Delft); Delft
- Delft University of Technology (TU Delft); today published
- Drexel University
- ETH Zürich
- Edmund Mach Foundation
- Fraunhofer Institute for Wind Energy Systems IWES
- KU LEUVEN
- Linköping University
- Linköpings universitet
- Loughborough University
- Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen
- Technical University Of Denmark
- Technical University of Munich
- Universidad de Alicante
- University of Adelaide
- University of Birmingham
- University of Bremen •
- University of Cambridge
- University of East Anglia
- University of Groningen
- University of Surrey;
- University of Trento
- University of Warwick
- Université Marie et Louis Pasteur
- Vrije Universiteit Brussel
- 34 more »
- « less
-
Field
-
on sufficient and sufficiently clean water. However, we often lack the data to fully understand the dynamics of contaminants throughout the urban water cycle. Existing sensors for water quality monitoring do not
-
description Cities depend on sufficient and sufficiently clean water. However, we often lack the data to fully understand the dynamics of contaminants throughout the urban water cycle. Existing sensors
-
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 3 months ago
be established for the combination of various optical sensor data sets covering different vertical, horizontal and temporal scales. Specifically the information on particulate and dissolved organic
-
the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
-
Autonomous Vehicles https://autolab.taltech.ee/ is a future-oriented research group with the main strengths and focus topics: Self-driving vehicles, driving algorithms and cyber-physical system Sensor fusion
-
of algorithms and digital neuromorphic hardware is an additional avenue for enhancing the efficiency of the methods. In this context the research will explore digital, event-based implementations
-
spanning design, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication
-
prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate
-
, machine learning or similar. Alternatively, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms
-
Join TU Delft and work together with NXP to build low-power AI accelerators for self-healing analog/RF calibration, fixing noise/offset. Co-design algorithms & hardware and validate on real silicon