16 algorithm-development-"Multiple"-"University-of-California,-Santa-Cruz" positions in Netherlands
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- University of Amsterdam (UvA)
- Eindhoven University of Technology (TU/e)
- University of Amsterdam (UvA); Amsterdam
- Wageningen University & Research
- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); today published
- Eindhoven University of Technology (TU/e); Eindhoven
- Eindhoven University of Technology (TU/e); today published
- European Space Agency
- Radboud University
- Wageningen University & Research; Wageningen
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that may empower consumers to resist persuasion and reduce harmful consequences? Are you passionate about advertising, algorithms and social media? Then apply for this PhD project focused on demystifying
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research project in collaboration with multiple tech companies to develop and demonstrate the next generation of free-space optical (FSO) communication systems for satellite communications. Information
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advance scholarship on who is most often exposed to algorithmic persuasion, how different types of people cope and are affected, and how we can develop remedies to reduce negative consequences. By doing so
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well as develop new algorithms for inverse scattering. These extensions will be employed in a reconstruction process on actual measured data from real-world metrology, in line with the long-term vision presented in
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collaboration with multiple tech companies to develop and demonstrate the next generation of free-space optical (FSO) communication systems for satellite communications. Information Satellite-based links
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genomic and biochemical diversity and thereby contribute to sustainable food and agriculture. As a group, we contribute to multiple BSc and MSc programmes. We educate new generations of biologists
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fascinated by electromagnetic modeling and numerical problem solving? Do you want to contribute to the development of state-of-the-art metrology for integrated-circuit production? Information Integrated
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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, which has multiple test machines with GPUs and AI accelerators. The algorithms used can be bound by the available compute power or memory bandwidth in different parts of the program. This information will
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turning point: decarbonization and independence of foreign fossil fuel are new requirements that drive the development towards a more distributed architecture, stochastic renewable generation units, smart