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with researchers at DTU and KTH, you will help develop an integrated decision-support system that: Uses real-time sensor data and AI models to assess risk scenarios. Dynamically recommends optimal
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analysis, the project will ensure the integration of the newest technological developments to enhance threat assessments and elevate intelligence studies with cutting-edge modeling. You should have an MSc
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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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. Knowledge of and working experience with modern exact methods such as AdS/CFT integrability, conformal bootstrap or localization will be considered an advantage. Our group and research- and what do we offer
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learning models achieve high performances on public datasets for single modalities, they are not adapted in practice. During this PhD project, the research will be focused on finding ways to integrate deep
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international conferences, is an integral part of the job. You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree in
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bioinformatics, AI and ML software tools to integrate and process the datasets quickly and efficiently. You will also work closely with other computational and experimental biologists to uncover new insights
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partners from Denmark and the Netherlands. Thus, these 2 PhD projects will be an integral part of a broader research team, consisting of collaborating partners with a common passion for autonomous
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updating and data extraction Work with quantitative data analysis, including meta-analysis Integrate living systematic review data into a RBA of sustainable dietary transitions Develop a living support
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system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models and machine