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Field
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, focus groups, surveys, ethnography, participatory mapping, and document analysis. To examine extreme weather event impact and management from the perspective of residents and stakeholders. The supervisory
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new nationwide AI system can be predicted using generated data sets of different sizes and measuring the environmental impact. This impact can be measured and calculated by our Software Energy Lab
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computational tools to support the safe and ethical deployment of AI in clinical settings. The research focus is on AI performance monitoring, distribution shift detection, bias assessment, and stress testing
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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements
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using statistical software. Prepares reports and presentations based on research findings. Collaborates with team members. Contributes to project discussions. Supports administrative tasks related
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Requirements 3 positions: English 1 position: Bilingual CBC/CBC Information on language requirements and self-assessment tests Assessment Criteria Candidates will be assessed on the basis of the following
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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using thermographic Non-Destructive Testing (NDT), a critical method for ensuring aircraft safety and reliability. NDT is increasingly vital in the aviation sector, enabling the detection of hidden
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. The project is co-sponsored by Spirent Communications, a world leader in navigation and testing technology. Spirent will provide advanced simulation tools, expert support, and industry placements to help make
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to reason about software (e.g., LLM agents for finding and fixing bugs) Static and dynamic program analysis (e.g., to infer specifications) Test input generation (e.g., to compare the behavior of old and new