10 algorithm-sensor-"University-of-Manchester" Postdoctoral research jobs at Carnegie Mellon University
-
project that involves designing microfabricated biomedical sensors and the readout circuitry for recording electrophysiology and electrochemical signals from biological samples. The overarching goal
-
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
-
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
-
. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
-
. Modeling dynamical systems Designing and extending algorithms grounded in probabilistic machine learning Applying statistical techniques to assess robustness and generalization. Development of methods
-
-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
-
/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
-
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
-
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
-
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