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Experience of research grant evaluation and administration Able to interpret complex research data and communicate it to lay audiences About us We value and respect every individual’s unique contribution
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opportunities to address the complex challenges of modern society, to develop comprehensive new approaches, and educate the problem-solvers of tomorrow from a multidisciplinary perspective. At the Faculty
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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of seed gene networks”. This project aims to use reverse genetics, cross-species complementation and single cell next-generation sequencing approaches to investigate how the gene networks that regulate
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renewable, benefits-eligible position. The University of Chicago Knowledge Lab leverages advanced computational tools to unravel complex scientific and societal problems, bridging the gap between data-driven
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opportunities to address the complex challenges of modern society, to develop comprehensive new approaches, and educate the problem-solvers of tomorrow from a multidisciplinary perspective. The Centre for Sport
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opportunities to address the complex challenges of modern society, to develop comprehensive new approaches, and educate the problem-solvers of tomorrow from a multidisciplinary perspective. The Faculty
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that combines structural biology, biochemistry, and cell biology. The lab is particularly focused on biomolecular interactions, characterizing regulatory complexes, and developing novel therapeutic
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Associate Professor of Experimental Physics Focusing on AI-Based Research of Biomolecular Structures
obtained and to solve complex macromolecular structures, the development and use of artificial intelligence and machine learning will increasingly be required. FAU and HZB are jointly appointing a
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of the domain, while the pre-processing step of geometry manipulation and mesh generation is one of the most important efficiency bottlenecks in such methods. The challenge is more prominent in modern, real-world