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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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materials, which are otherwise inaccessible to material scientists? At DTU Energy, our research is targeting exactly this, and to reach these goals, we are looking for a PhD candidate to work at the interface
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at the interface between chemical engineering, data science, and semantic web technologies. The work will be tightly integrated with other digitalization activities at DTU Chemical Engineering. Responsibilities and
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an optimized extraction process for bioactive compounds from seaweed. Analyse and characterize the extracted compounds for their bioactivity and techno-functional properties. Support student supervision and
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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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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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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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Job Description Do you want to do research on cutting-edge machine learning methods? If you are establishing a career as a researcher in machine learning, and you are motivated to work with the