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and data-driven framework for structural condition assessment to support resilience-oriented decision making in offshore marine infrastructures. An accurate and fast (near real-time) damage detection
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the Research Group for Genomic Epidemiology. By joining us, you'll gain expertise in AI, bacterial sequence analysis and food safety evaluation while contributing to one of the most challenges in food safety
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landscapes. Research Project & Objectives This PhD project aims to develop a physics-informed and data-driven framework for structural condition assessment to support resilience-oriented decision making in
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pre-training earlier), as well as in counterbalancing bias & overfitting. In addition to classical XAI models, e.g. decision trees, there is the paradigm of commonsense knowledge (CSK), i.e. everyday
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models to detect food safety compliance risks Integrate regulatory, environmental, and microbial data from food SMEs Design user-friendly decision support systems for inspectors and producers Co-create and
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, what motivates them to engage with disruptive technologies, and how emerging regulatory frameworks and business models influence their decisions. The doctoral research will focus on mapping the diffusion
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, Responsibilities and qualifications Electricity markets are undergoing a rapid transformation: Market participants are deploying AI algorithms towards making their bidding decisions. AI algorithms are instructed
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
personalized learning for improved instant decision making. Key beneficiaries are expected to be construction industry stakeholders, for example, project owners, architects, engineers, site management (incl
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behaviour and provides active personalised learning for improved instant decision making. Key beneficiaries are expected to be construction industry stakeholders, for example, project owners, architects, engi
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
behavior and provides active personalized learning for improved instant decision making. Key beneficiaries are expected to be construction industry stakeholders, for example, project owners, architects