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the power of direct sequencing and AI to provide rapid, accurate detection and characterization of pathogens, enabling risk managers in the food industry to make better-informed decisions. Your primary tasks
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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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, 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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Job Description The SDU Center for Energy Informatics is pleased to announce 3-year PhD positions in AI-driven decision support and digital solutions for sustainable energy and industrial systems
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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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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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, 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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decision-making in chemical engineering research and teaching. To support this effort, we invite applications for 1-2 PhD students (3 years). You will become part of a small, cross-disciplinary team working
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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