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Field
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-relevant issues and offer you the opportunity to actively shape change! We offer you optimal conditions for the successful completion of your doctorate: The opportunity to complete a doctoral thesis within 3
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clocks and laser links between Earth and the international space station ISS. The concrete task is to optimize our strontium lattice clock (DOI: 10.1103/PhysRevA.98.053443), transfer it to the Geodetic
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techniques. This research proposes a novel framework that integrates Machine Learning (ML) for structural health monitoring (SHM) and design optimization of CFDST wind turbine towers. The study will focus
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quantum computing as well as experience with cryogenics, signal delivery, microfabrication, materials optimization, and microwave control are highly preferred qualifications Please feel free to apply
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on generating new knowledge for optimizing biological conversion of carbon dioxide to acetic acid in close collaboration with an industrial end-user of the developed technology. Responsibilities and tasks Your
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Optimizing a 3D microfluidic IVD model to study cell responses to wear particles, refining culture conditions, and analysing cytotoxic and inflammatory mechanisms. Optimizing a 3D microfluidic IVD
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objective is to surpass the current traditional thermodynamic and optimization approaches, which are constrained in design discovery capabilities and long-term TES performance evaluation. Through your
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Memorial Sloan-Kettering Cancer Center | New York City, New York | United States | about 2 months ago
critical quality attributes Optimize design and process parameters to ensure efficient production of highly potent mRNA Evaluate multiple DNA-based platforms for optimal mRNA potency and process parameters
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will focus on building understanding of the interplay between the upstream process parameters and process performance to develop approaches and strategies to optimize efficiency and robustness and allow
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become the bottleneck in achieving optimal performance and trustworthiness. This project will focus on how a federated multi-task learning framework can be effectively designed and optimised to address