75 web-programmer-developer-"https:"-"https:"-"https:" research jobs at Carnegie Mellon University
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persuasion Building user-facing tools or running interventions at scale AI safety research (especially related to deception, manipulation, or evaluation) Computational text analysis, web development
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work environment. We are seeking creative and upbeat Research Assistant that will assist in the development and execution of research projects including experiment design, analysis of data collected and
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high school student who will support data analysis, application development, and research objectives. Work could include, for example, software development, investigation and summary of existing research
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understanding of placental development through the integration of computational modeling and clinical imaging data within the Biomedical Flows Simulation and Multiscale Modeling (BioSiMM) Lab. Core
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records. Responsibilities: Drone development and deployment. Field testing and data analysis. Follows research plans in order to collect, record, and manipulate research data. Maintains accurate and
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-long learners in the fields of cybersecurity, AI/ML, or related areas, who are willing to cross-train to address AI Security. As part of the Threat Analysis Directorate, you will join a group of security
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-long learners in the fields of cybersecurity, AI/ML, or related areas, who are willing to cross-train to address AI Security. As part of the Threat Analysis Directorate, you will join a group of security
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candidate is a highly motivated high school student who will support data analysis, application development, and research objectives. Work could include, for example, software development, investigation and
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records. Responsibilities: Assist in the research and development of a large model for 2D navigation. Design, execute, and document experimental evaluations to validate model performance. Design and
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for the Pitkow Lab. Core Responsibilities Include: Develop computational methods for inference and control that improve the reliable and efficient operation of autonomous agents in complex, uncertain environments