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significantly slows down the development of new desirable nanostructures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
nano-structures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA nanoconstructs. The primary goal is to build an AI
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PhD Position - Organic Electrosynthesis: monitoring of reaction transients with real-time techniques
for selected electro-organic transformation in detail: Design, validation and verification of online and offline analytical methods Design, synthesis, and characterization of catalytic materials Utilization
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design are often too slow, costly, and inefficient to cope with the increasing complexity of performance and resource-efficiency requirements. This collaborative doctoral project brings together
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Your Job: Design and development of an in-house X-ray beamline for long term operando investigation of chemical hydrogen storage reactors Unravelling of relationships between catalyst structure and
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interdisciplinary collaboration. That’s why our projects are designed specifically to connect diverse scientific fields and foster cross-institutional collaboration, enabling you to benefit from the combined
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and curate LC-MS/MS data for high-quality feature extraction Design and train machine-learning models for mass spectrometry and chemometric data Integrate multi-omic data including genomics and
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DM Best Applied and Best Theoretical Paper Awards. Beyond academia, Dr. Li has extensive industrial experience and collaboration with Microsoft, The Bell Labs, Hong Kong Mass Transit Railway Co., and
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interactions, such as the demand for agricultural products from regions like the EU. This research will inform the design of effective and equitable environmental policies. Key responsibilities: development
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. Transition metal-based complexes, in particular, offer rich spin properties that can be tailored through ligand design. This project aims to explore and optimize such molecules to enhance their performance as