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Postdoc Position for Computational Genomics, AI Precision Oncology, Cancer Biology and Immunobiology
University of Pittsburgh, Pittsburgh , Pennsylvania, US | Pittsburgh, Pennsylvania | United States | 2 months agomechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights
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collection in Morocco forthcoming. Building on these insights, the project is expanding its quantitative component across Morocco, Tunisia and Egypt, combining survey research and embedded survey experiments
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results as well as actionable insights for the project's partners and pilot sites. Candidates may come from marketing, consumer behaviour, psychology, behavioural economics, environmental psychology
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computer science, explainability is mainly evaluated through data-driven metrics. While they provide some insights for developers, it is unclear whether existing metrics track any ethically relevant properties
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of conceptual insight for the contemporary physics and mathematics in the project. The open and safe environment at Radboud University is extremely inspiring. I’ve felt totally at home here for over
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interpret dynamic visual signals. The successful candidate will contribute to experimental design, computational analysis of behavioral data, and the integration of biological insights with robotic systems
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insights into practical applications, but also the other way round; Collaborate and exchange with the involved researchers at the Haagsche Hogeschool and Erasmus University Rotterdam; Organise and facilitate
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with an international team, establish experimental designs, and provide biological insight into the mechanisms of chromatin recognition and repair. The postdoc is expected to drive the project, including
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-edge machine learning methods with empirical insights from the educational arm of the project. A central technical challenge guides this position: How can an LLM-based AI social agent be designed, fine
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, and substantive empirical insights relevant to the design and operation of mass transit systems. The primary objective of the role is to develop, extend, and apply rigorous statistical and computational