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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 Department Summary
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Responsibilities: Conduct programming and software development for graph data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations
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workflows — including methods for knowledge graph construction, advanced querying, and data quality assurance. Contribute to aligning the developed methods with emerging standards for information modelling
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representation methods for accelerated inverse design Large language, diffusion & graph neural models for materials discovery Fine tuning and architecture optimisation of foundation models Inverse design of next
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and synthesis of new materials. You should have a PhD in a relevant field (Computer Science, Mathematics are most likely to fit the role, but we are open to Chemistry, Materials Science, Chemical
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. Demonstrated high level of written and oral communication skills. Preferable Experience in eukaryotic cell culture/tissue culture Expertise with advanced graphing and/or data analysis software (Prism, Origin Pro
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PhD in a relevant field (Computer Science, Mathematics are most likely to fit the role, but we are open to Chemistry, Materials Science, Chemical Engineering, etc.), expertise in cutting-edge AI and
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PhD in a relevant field (Computer Science, Mathematics are most likely to fit the role, but we are open to Chemistry, Materials Science, Chemical Engineering, etc.), expertise in cutting-edge AI and
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background in systems thinking, analysis and modelling Experience in teaching and supervision in higher education at least on MSc level Knowledge of graph theoretical approaches and graph signal processing
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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