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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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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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Knowledge Graphs. Our key objective is to hire a recently conferred PhD with outstanding qualifications and core values of high standards of excellence in innovative research. Benefits at UTA We are proud
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• Holding a PhD in Computer Science with a focus on Natural Language Processing. • Knowledge Graphs with strong publication records. Preferred Qualifications • Demonstrated mentoring experience. Special
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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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interaction, (vi) Network Science. The ideal candidate is self-motivated and hard-working with a PhD in one of the following: Data Science, Computer Science, Computational Social Science, Information
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inequality, (iv) diversity, (v) online controlled experiments, and (vi) network science. The ideal candidate is self-motivated and hard-working with a PhD in Data Science, Computational Social Science
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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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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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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