Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- European Space Agency
- University of Amsterdam (UvA)
- Leiden University
- Wageningen University & Research
- University of Groningen
- Utrecht University
- Centrum Wiskunde en Informatica (CWI)
- Radboud University
- SRON
- Tilburg University
- AMOLF
- Amsterdam UMC, location VUmc
- Erasmus University Rotterdam
- Erasmus University Rotterdam (EUR)
- Sanquin Blood Supply Foundation (Sanquin)
- The Open Universiteit (OU)
- Universiteit Leiden
- University of Twente (UT)
- 10 more »
- « less
-
Field
-
, including bioacoustics algorithms developed in the team. What you will do Conducting rigorous research at the intersection of ML and wildlife bioacoustics; Actively participating in regular group and one
-
knowledge of system security engineering, crypto algorithms and certification processes. Good knowledge of technology development and maturation processes relevant to PRS, security and crypto devices
-
), Computer Science (Machine learning, Efficient Algorithms and High Performance Computing), and Physics (Image Formation Modelling). Your project is part of the DUAL-IMPACT project, which focuses on the development
-
(Automated Design of Algorithms) group in the machine learning clusters at LIACS, Leiden University, and supervised by Jan van Rijn and Holger Hoos. You will be working intensely with other project members
-
master's degree in computer science, mathematics, or related subjects. A solid background in cryptography, algorithms, discrete mathematics, or a related area. Strong analytical and problem-solving skills
-
to operate in a scalable and decentralized manner while achieving obstacle avoidance using onboard sensing and adapting to changes in dynamic environments. In parallel to the theoretical and algorithmic
-
, development and implementation of digital signal processing algorithms and data processing strategies for microwave radiometers; conducting laboratory activities to validate architectural concepts, operating
-
identify those with the highest potential for early adoption in space engineering; translate theoretical advances into algorithmic innovations, design principles and prototype tools that can be integrated
-
operation will be studied. From a methodological perspective, the above research challenges will be tackled through a mix of theory, algorithm design, and analysis of experimental data, partly collected by
-
different incentives, mechanisms and regulatory scenarios, evaluating their performance with respect to different objectives and their trade-offs. Developing decentralized and bi-level algorithms to help