675 engineering-computation-"https:" "https:" "https:" "https:" "https:" "U.S" "U.S" positions in Netherlands
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procurement processes Project and programme management skills Space engineering and systems orientation Good knowledge of the life cycle thinking approach and ecodesign/life cycle assessment techniques Ability
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circular wind energy sector. A key component of this mission is developing predictive "look-ahead" control capabilities based on LiDAR technology. Your Mission: Advanced LES & Research Leadership As a
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Programme Department, Directorate of Navigation. You will be responsible for supervision of the platform design, development, implementation and validation of the G2SB1 Galileo 2nd Generation satellites
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Safety Office, Quality Department, Directorate of Technology, Engineering and Quality. You will work as a Product Assurance and Safety Manager to support projects in the Connectivity and Secure
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remote sensing technology and real-time turbine control. Your focus will be the development of a predictive capability that allows turbines to react to the wind before it hits the blades. Using upstream
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meaningful contribution to computational social science research in the Netherlands. You collaborate with other researchers to design and develop a wide range of innovative projects, for example involving
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personalized management of cardiovascular and respiratory failure. About the organisation The Faculty of Science & Technology (Technische Natuurwetenschappen, TNW) engages some 700 staff members and 2000
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about the incoming projects and making use of the group’s expertise and technology to execute the projects effectively. While many of your projects will be initiated by collaborators, there is space and
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databases and digital collections (such as newspaper archives, policy documents, and media sources) and apply techniques such as crisis event detection, computational narratology, and semantic modelling. In
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to genomic and epidemiological data; design controlled computational experiments (simulations and synthetic datasets) to validate theoretical predictions; apply your methods to large-scale viral datasets