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simulation methods and scientific software development. The successful candidate will contribute to research and development on: EMT simulation of future power systems. Simulation methods for converter
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-constrained devices such as wearables, smart sensors, hearables, and IoT nodes. While current deployment methodologies can optimize models before deployment, the resulting software remains static throughout
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hardware-software co-design of ML models taking inspiration from the brain. The applicant should: have a Master’s degree in Engineering with a background in Electrical Engineering, Computer
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the development of predictive network intelligence for integrated terrestrial and NTN systems. In its first phase, the candidate will contribute to the development of a software-defined radio-based spectrum sensing
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this additional qualification.-You have strong skills in statistical, econometric and quantitative data analysis and have experience with statistical software packages; furthermore, you are keen to develop
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stability assessment of converter-dominated transmission systems. The research combines power systems, numerical methods and scientific computing, with a strong emphasis on software development and practical
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. • Education: You do not hold a doctoral degree. You hold a Master’s degree in software engineering, ICT, computer science, game development, or related fields obtained with at least distinction (cum laude
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of the Division of Agricultural, Food and Resource Economics. You have experience with or are eager to work with large databases and database management software. You have starter skills in statistical, econometric
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and light-scattering modalities within a single instrument, bridging this gap. The project is multifaceted, ranging from optical and optomechanical designing and instrument construction, to software
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research methods, including behavioural, psychophysiological, hormonal, and molecular approaches. Has an affinity for quantitative research methods and data analysis (experience with statistical software