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Field
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(CPS) for aquaculture, to sensors and platforms for maritime applications. The Postdoc’s primary task will be to lead the development of algorithm, software, and hardware to extend the current HAUCS
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. Develop and implement control algorithms for distributed multi-agent system operations and spacecraft-based robotic manipulation. Perform research on spacecraft dynamics and control, including trajectory
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vehicle (AV), allowing for automated detection, prediction, mapping, and planning. During the vehicle’s operation, data is obtained through a myriad of sensors in an AV—including RADAR, LIDAR, cameras, and
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research team. Key research areas include: Development of low-carbon materials and tunable thermal energy storage materials integrated with smart sensors and advanced algorithms Creation of Digital Twins
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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logistics. Develop and implement control algorithms for distributed multi-agent system operations and spacecraft-based robotic manipulation. Perform research on spacecraft dynamics and control, including
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for the development of a sensor technology to detect microRNAs in biological samples. Specifically, the PRF will fabricate sensor on a paper platform and qualitatively and quantitatively test microRNA presence in
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to remove PFAS. To accomplish these goals, the candidate will participate in the development of AI/ML algorithms for the prediction of chemical properties, infrared and mass spectra, and ionization cross
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sensors will be designed, modeled, fabricated, and fully packaged for deployment. Sensor performance will be measured in the lab and new techniques will be developed to characterize performance for inertial
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, including autonomous robotic systems for In-space and On-orbit Servicing, Assembly, and Manufacturing (ISAM and OSAM) and space logistics. Develop and implement control algorithms for distributed multi-agent