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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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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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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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, synthesis, and characterization of silicone-based foams for innovative healthcare applications. Key tasks will include tailoring the chemistry and processing of silicone polymers to create controlled foam
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Job Description Do you want to contribute to a greener future where state-of-the-art scanning nitrogen vacancy (NV) magnetometry is introduced to visualize buried functional processes in energy
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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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effective enzymatic recycling processes. We are looking for candidates with strong qualifications in some of the following areas, and a motivation to develop within others: Protein chemistry Enzyme kinetics
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and operation of building HVAC systems, these technologies support both energy efficiency and flexible demand objectives. Model predictive control (MPC), which involves physics-based building energy
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funded PhD scholarships (3-year employment) in a vibrant interdisciplinary research environment. The positions are part of the research project “AI-driven materials optimization for light trapping in thin
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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