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with PV generation. The research will contribute to developing management and real-time operation tools to coordinate and optimize charging with PV production, while also enabling grid services
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the research group Bioactives Analysis and Applications, and as part of the prestigious Alliance PhD program, you will collaborate with the Technical University of Munich (Germany). If you're ready to
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latest predictive and generative AI for materials, we can offer you the best possible foundation. We seek two highly motivated and talented PhD students to join our group at DTU Compute, and we offer
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the redistribution of the phases present, reaction mechanisms will be investigated and the information gained will be used for optimization of the battery. The position is part of the INCEPTION Doctoral Network
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skills and a keen interest in data-driven research. Your role will be to apply the developed semantic infrastructure to concrete case studies—such as cross-unit scheduling, process optimization
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pharmacology. The PhD project will focus on testing and optimizing antisense oligonucleotides in preclinical in vitro models, as well as formulating these molecules into a novel biodegradable delivery system
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The primary tasks will be to: Synthesize thin films of solid-state battery components, following established protocols. Optimize the sensing schemes of a new state-of-the-art commercial scanning NV magnetometer
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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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structures, followed by thorough characterization of their chemical, structural, and mechanical properties. You will work on understanding and optimizing foam properties such as porosity, elasticity, and
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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