17 evolution-"https:"-"https:"-"https:"-"https:"-"https:"-"BioData" Postdoctoral positions at Carnegie Mellon University in United States
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generating human language in both written and spoken forms. We are seeking a Postdoctoral Research Associate. This position conducts a broad range of activities in the development and analysis of commercial
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generating human language in both written and spoken forms. We are seeking a Postdoctoral Research Associate. This position conducts a broad range of activities in the development and analysis of commercial
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the development of microfabricated devices and integrated measurement systems from concept through validated laboratory demonstration for an exciting project on microneedle-array-based diagnostics. In this role
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may involve organizing and implementing complex research plans, the development of methods of research, testing and data collection, analysis and evaluation, and writing reports which contain
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, engineering, and development responsibilities as assigned by the supervisor Adaptability, excellence, and passion are vital qualities within Carnegie Mellon University. We are in search of a team member who can
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with device/electronics teams Other research, engineering, and development responsibilities as assigned by the supervisor Adaptability, excellence, and passion are vital qualities within Carnegie Mellon
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on engineering development for healthcare applications, integrated AI, and related projects. Core Responsibilities: Conduct independent and collaborative research aligned with the themes above Guide graduate and
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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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. This project provides a vibrant learning environment for all the trainees. The PI is committed to the professional development of the postdoc associate in addition to their technical excellence. Core
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Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods of research, testing and data