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graphics programs, library search programs, graphing and statistical analysis programs, and Laboratory Information Management and Quality Assurance programs. Preferred Qualifications BS degree in
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the doctoral level. More than 20 percent of its 25,000 students are enrolled in graduate course work, studying in disciplines ranging from atomic physics and graph theory to medieval literature and blind
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25,000 students are enrolled in graduate course work, studying in disciplines ranging from atomic physics and graph theory to medieval literature and blind rehabilitation. Of 101 graduate offerings
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essential for learning complex distributions over structured data such as text, graphs, and biological sequences. Developing and understanding models for dis- crete spaces is therefore a key challenge in
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qualification. Professional assignment: Chair of Scalable Software Architectures for Data Analytics (Prof. Dr. Michael Färber) Research areas: Natural Language Processing, Large Language Models, Knowledge Graphs
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., precision functional mapping, graph theory, hierarchical clustering, etc.) to clinical brain imaging data. This position provides an excellent opportunity to contribute to research that bridges systems
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Carolina is inviting applications of two postdoctoral associates in the area of mathematical foundations of data science, AI, Graph Theory, Optimization, Probability Theory in a broader sense. The candidates
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project Can AI interpret graphs like a human materials scientist that relates diagrams to composition temperature, pressure, synthesis, processing and uncertainty? The PhD candidate will develop and
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: Design and implement AI/ML pipelines for multi-omics data integration, including supervised and unsupervised learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph
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implement AI/ML models (e.g., graph neural networks, transformer-based models) for retrosynthetic pathway prediction. Apply deep learning techniques to predict reaction outcomes, optimize reaction conditions