22 evolution "https:" "https:" "https:" "https:" "https:" "https:" "Aix Marseille Université " Postdoctoral positions at Carnegie Mellon University
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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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. 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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multidisciplinary team tackling critical issues in cancer detection and provide support in the applied nanotechnology lab to assist in the development and execution of research projects related to the production 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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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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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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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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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
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. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods