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, simulation, prototyping, and pre-clinical validation of a novel temperature-insensitive, 6-degree-of-freedom force sensor for use in minimally invasive cardiac surgical instruments. This patented technology
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: Department of Mathematics and Statistics Position Summary : Optimize ML RNN/CNN models on sensor data with healthcare applications. Help interdisciplinary researchers to publish clean codes in public
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of deep learning algorithms. Outstanding programming skills in Python. Extensive experience working on one or more of the following areas: image processing, machine learning, and patient records. Track
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data sources such as UK Biobank and eventually come up with algorithm useable for the early detection of Alzheimer’s disease (AD) and Parkinson’s disease (PD). Nature of Work: In this project, we will
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candidate will support experimental research focused on the synthesis and characterization of photo-activated semiconductor materials. Responsibilities include developing and testing UV-activated gas sensor
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characterization of photo-activated semiconductor materials. Responsibilities include developing and testing UV-activated gas sensor prototypes, conducting laboratory and field evaluations, and analyzing
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multimodal data (video, self-report, physiological sensors, automatic facial recognition software) that examines CER in multiple contrasting contexts. And (3) Advance educational theory and practice by
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environmental data Processing and analyzing large-scale remote sensing datasets from UAV, satellite, and ground-based sensors Leveraging artificial intelligence, e.g. machine learning, reinforcement learning
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signal processing algorithms on FPGA, optimized to significantly improve the resolution of real-time energy measurements made by the ATLAS Liquid Argon Calorimeter system. Use novel high-level synthesis
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degree in Computer Science, Math, Statistics or Engineering programs. Ph.D would be an asset. Knowledge of classification algorithms, vision-language models (VLM) and Hugging Face Transformers is an asset