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Field
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related field Sound knowledge in the field of artificial intelligence and machine learning Ideally experience with knowledge graphs, semantic search, graph neural networks (GNNs), explainability
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continuation of scholarly activity and research after achieving the PhD or other doctoral degree under the direction of a senior faculty member who serves as a mentor for the postdoctoral appointee. Additional
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packages, computer coding, and statistics is highly desired. Past research assistants have been accepted to strong PhD programs in clinical and experimental psychology, epidemiology, and medical school
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be expected to seek external funding. The Department has a strong PhD program in Statistics, Graph Theory, Combinatorics, and Applied Mathematics, with very active research collaborations with other
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high throughput cellular assays. Perform statistical analysis and proficiently use graphing software or R scripts. Successful Candidates Will Have: Experience in analysis of protein kinases
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well as methods for inferring genealogical structures such as ancestral recombination graphs (ARGs) and leveraging them to study heritable traits and human evolution. Applicants should hold a be near completion of
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mechanisms of online media platforms by granting users full control over their sensitive information. Innovation. To meet users' varying privacy demands, this project put forward a graph-based user
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of the College of Engineering in the development and preparation of research. This will entail working with teams of PhD-level researchers and staff to conceptualize and draft research proposals. This position
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and use machine learning methods (mainly graph neural network architectures) to design representations and transferable energy models for proteins and materials. The position will serve to develop your
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, and clinical safety datasets Implement graph-based retrieval-augmented generation (RAG) methods to enhance knowledge extraction and information synthesis Develop cross-pathway analytical methods using