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Reconfigurable/Spatial computing architectures, such as FPGAs, CGRAs, and AI accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs
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education. Specifically, the tasks are: Design, implement and validate a tool to collect and analyze learning demands of learners. Design, implement and validate a modular software architecture that can
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team consisting of scientific staff and PhD candidates from different disciplines and will collaborate with a small team of software developers working on AI prototypes and the required supportive
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detection and management, such as code exposure, coverage, and secure patching/update architectures as part of DevSecOps processes; Validating mission data system software interfaces and service-specific
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to obtain one; Knowledge of designing and managing Internal Developer Platforms or cloud-native architectures; Experience with infrastructure-as-code tools such as Terraform or Ansible, and a declarative
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and understanding of ML and AI architectures for hardware and software implementation Understanding of FDIR concepts, as applied in on-board space systems Understanding of avionics and onboard data
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architecture); Advanced SQL skills for handling complex queries; Experience with data governance, process design and automation; Microsoft Power BI Data Analyst Certification, or you are willing to obtain one
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the Table Representation Learning Lab and is member of the Database Architectures group. Prior to joining CWI, she was a postdoctoral fellow at UC Berkeley after obtaining her PhD from the University
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Centrum Wiskunde & Informatica (CWI) has a vacancy for a 4-year PhD position (m/f/x) on the subject of Reliable AI-powered Data Analysis in collaboration with the University of Amsterdam. Interested