Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Delft University of Technology (TU Delft); Delft
- Delft University of Technology (TU Delft)
- University of Twente
- University of Groningen
- CWI
- University of Twente (UT)
- Utrecht University
- Delft University of Technology
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); Eindhoven
- Leiden University
- Maastricht University (UM)
- Maastricht University (UM); Maastricht
- University of Twente (UT); Enschede
- Utrecht University; Utrecht
- Vrije Universiteit Amsterdam (VU)
- Wageningen University and Research Center
- 7 more »
- « less
-
Field
-
, as well as satellite and sensor data, looking specifically at 6 different use cases across Europe. In addition to the detailed innovative analysis of existing methods and protocols, ITC will focus
-
faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies
-
lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future
-
to simulate cascading disaster effects, as well as satellite and sensor data, looking specifically at 6 different use cases across Europe. In addition to the detailed innovative analysis of existing methods and
-
: How does decoherence emerge in complex quantum systems? Can we emulate and study complex many-body physics? Can we use quantum coherence to realize novel improved sensors? Can we protect quantum states
-
inference algorithms as well as proofs of their correctness and efficiency) and systems (e.g., high performance, functional array programming DSLs) to tackle challenging probabilistic and differentiable
-
) and systems (e.g., high performance, functional array programming DSLs) to tackle challenging probabilistic and differentiable programming applications (e.g., experimental design, machine learning
-
, functional array programming DSLs) to tackle challenging probabilistic and differentiable programming applications (e.g., experimental design, machine learning for science). We do so by bringing together a
-
we use quantum coherence to realize novel improved sensors? Can we protect quantum states and computations indefinitely so that large-scale quantum computations become possible? And does quantum
-
interventions using AI? Join us to turn real-world sensor and app data into smarter, personalized digital solutions that support behavior change. PhD Candidate Predicting Adherence to Digital Health-Promoting