12 algorithm-sensor-"University-of-Gothenburg" Postdoctoral positions at Carnegie Mellon University
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project that involves designing microfabricated biomedical sensors and the readout circuitry for recording electrophysiology and electrochemical signals from biological samples. The overarching goal
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considered. You should demonstrate: A strong foundation in micro- and nanofabrication, materials and surface modification, and sensor integration, along with competence in electronics, data acquisition, 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
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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
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-on expertise with assembly and sealing of small-scale fluidic systems. General knowledge of sensors and electronics, sufficient for close collaboration with chemistry and electronics teams, is preferred
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/calibration are essential Working literacy in sensor/electronics integration and close collaboration with device- engineering teams General knowledge of nucleic acid sensing, CRISPR methods, and electrochemical
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members. Participate in traffic scenario generation project and pedestrian modeling project. Develop sophisticated AI-driven algorithms that create realistic, safety-critical test scenarios for autonomous
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algorithmic fairness Formulation of new problems and research directions and translating topical issues into algorithmic problems Designing new algorithms and investigating their performance on synthetic and
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algorithmic fairness Formulation of new problems and research directions and translating topical issues into algorithmic problems Designing new algorithms and investigating their performance on synthetic and