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: Appropriate research areas may include but are not limited to: Development and utilization of rapid, inexpensive, and/or in situ sensors for real-time detection of chemical hazards e.g., allergens, heavy metals
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involves planning and executing aquatic field operations, piloting AUVs and ROVs, deploying buoys and other sensors, and contributing to data collection and processing across all five Great Lakes
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(BAS). Instruct students on the principles, architecture, and functions of sensors, controllers, actuators, and communication networks within BAS. Guide students in identifying common BAS hardware
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Responsibilities: To assist in developing multimodal algorithms that can detect early signs of depression from speech and text information. To assist in designing, developing, and acquiring voice and text corpus
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data retrieval, interface with multiplexers and sensors. Demonstrated proficiency with eddy covariance instrumentation, and ecophysiological field instrumentation. In particular, candidate has worked
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, Hugging Face etc., in applied problem-solving contexts. Understanding of machine learning algorithms (gradient descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers
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healthcare application needs to analyze sensitive patient data across distributed nodes. Researchers and students can explore privacy-preserving algorithms and technologies like federated learning and zero
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systems, multi-function radar, AI/ML algorithms rely on high performance digital signal processing and real-time computing to provide high-fidelity results in an actionable timeframe. The ARRC intends
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. Requirements: • Bachelor's degree in computer science or equivalent knowledge Desirable: • Knowledge and practical experience in areas such as algorithms, data structures, software engineering, artificial
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Overview Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and