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the ambitions to accelerate the detection and optimization of sustainable chemical approaches through the development of novel reactions and advanced analytics using state of the art high-field and hyperpolarized
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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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Method to analyze the single-photon source performance (PhD1). Optimize and propose new single-photon source designs overcoming these limitations to be fabricated by other PhD students (PhD1). Perform
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
feedback, and real-time agent-based simulation for guiding optimal work performance. Following smart serious gaming approaches, novel artificial intelligence forecasts human behavior and provides active
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intelligence (AI) to optimize large dataset analysis, improving decision-making processes for awarding grants to firms and scientists. Key research areas include: Enhancing Selection Decisions: How can we make
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the optimization of bioactive compound extraction from various seaweeds for the development of fortified foods. This PhD position aims to (i ) identify suitable seaweed species for high-yield protein extraction, (ii
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available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. MPCs excel in handling constrained optimizations and new operational conditions, whereas RLs
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and kinetic modelling Expression, purification, and characterization of enzymes from fungal and bacterial sources Development and optimization of enzyme assays Structure–function studies of enzymes
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
for realistic haptic control and feedback, and real-time agent-based simulation for guiding optimal work performance. Following smart serious gaming approaches, novel artificial intelligence forecasts human
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academic partners in Europe and globally. Candidates with the following qualifications will be preferred: Educational background in power systems. Documented knowledge in optimization in power and energy