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benefits package that includes: holidays, vacation and sick time; health, dental and vision insurance; life insurance; short and long term disability insurance; a tuition waiver program for employee and
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curious to deliver work that matters, your journey starts here! The Department of Electrical and Computer Engineering (ECE) ranks among the best in the country. Our research programs are at the forefront
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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learning with a background in robust and embedded control, aerospace systems and physical modelling, as well as in artificial intelligence-related concepts, computer vision and numerical optimisation
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-reviewed publications. Prior experience with biological network analysis and practical application of a variety of machine learning and computer vision techniques is preferred. The successful candidate will
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. The NOAHS Lab is led by Prof. Alan Wang (alan_wang@baylor.edu), who is the Mearse Endowed Chair Professor at the Department of Electrical and Computer Engineering. During his research career, Prof. Wang has
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planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and manipulation strategy adaptation Real-world
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curious to deliver work that matters, your journey starts here! The Department of Electrical and Computer Engineering (ECE) ranks among the best in the country. Our research programs are at the forefront
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profiles, to identify treatment response patterns, subtypes, and critical intervention windows that reduce Alzheimer's risk Disease (AD) risk. This position will involve applying machine learning, deep
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of these patients. The goal of this project is to combine cutting-edge multi-omics technology, data analytics, machine learning and clinical samples from the human eye to decipher new insights into disease mechanisms