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Field
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ability to work both independently and as part of a team Preferred Qualifications Experience in graph-based AI models, multi-omics data integration, or network inference Background in epigenomics, gene
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, and maintaining a system to track proposals. Evaluate and perform preliminary analysis of the data using graphs, charts or tables to highlight the key points of the research results collected in
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Associates. The ideal candidates will possess a doctoral degree (PhD or MD) and have a strong background in molecular biology and physiology. There are three major projects in the lab: 1) studying the role
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independently, has a passion for AI and its applications, and is willing to learn new technologies. The candidate should have a PhD in Computer Science or a closely related field. Relevant background and skills
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. Mathematically, a network is represented by a graph, which is a collection of nodes that are connected to each other by edges. The nodes represent the objects of the network and the edges represent relationships
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a particular topic mentioned above. Applicants should meet the following qualifi cations and possess relevant expertise: A PhD in Computer Science or a closely related field, with specialization in
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of the university. Applicants must be within five years of receipt of their PhD to be considered for initial appointments and subsequent renewals. About the School of Mathematical and Statistical Sciences (SoMSS
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these solutions against explicit, formalized constraints by symbolic reasoning. An example is a LLM translating natural language specification into a symbolic representation (e.g. knowledge graph (KG) or logic
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by professor Krzysztof Janowicz consisting of international researchers including PhD students, postdocs, faculty, scientific programmers, and other project personnel with a diverse set of backgrounds
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data reflect real‑world disease phenotypes. Advanced analytics: apply AI and machine‑learning techniques (e.g., graph neural networks, multimodal transformers) to uncover novel biomarkers and generate