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and summary reports of all procedures and results including graphs, scientific calculations, and statistical analysis charting. May be responsible for tissue & cell culture activities. May be
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visualization environments Optimize scene graphs, memory management, asset streaming, and runtime performance Contribute to research proposals and peer-reviewed publications Generative AI Integration Generative
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Force Microscopy. Electroactive biomaterial experience, including electrochemical characterisation and synthesis. Expertise with advanced graphing and/or data analysis software (Prism, Origin Pro, Matlab
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, Distributed Ledger (blockchain), Language Technologies, Mixed Reality, Recommender Systems, Distributed Systems and Graph Theory. A full list of computer science faculty members is available here: https
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pangenome graphs, and identify trait-associated structural variants. Moreover, we have developed imputation methods that provide accurate genotypes in pedigreed populations, and haplotype-based association
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ability to bring these tools to bear on problems in data analysis and complex systems. Experience designing and implementing mathematical measures of complex systems, ideally on graph- or simplicial-complex
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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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researchers with interpretation of statistical test results. Creates graphs, tables, charts to depict results. Develops narrative descriptions of results for policy articles, journal articles and grant
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License: No If yes, what is the preferred licensure/certification?: Preferred Computer Applications: Preferred Other Computer Applications: Graphing software Preferred Additional Knowledge, Skills and
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | about 2 months ago
the form of graphs to analyze and predict food-effector systems. Key Responsibilities Develop Probabilistic Machine Learning Models to integrate graphs and food-related omics data Multi-omics integration