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Field
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applicable to the position: Developing, testing, and analyzing research related to chemical sensing technologies in water; designing, fabricating, and optimizing sensing platforms and functional materials
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of Alabama and beyond. The successful candidate will apply tools including (but not limited to) Data Acquisitions, Data Mining, Data Visualization, Machine Learning, Statistics, Optimization and Simulation in
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and wave-equation–based modeling, including familiarity with adjoint-state methods, gradient-based optimization, and multi-scale inversion strategies. Proven expertise in machine learning and deep
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control and statistical analysis Learn about optimizing liquid handler to automate biomolecule assembly on electrodes Participate in development of techniques for high throughput optimization of sensing
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do: Design, fabricate, characterize, and optimize electrochemical biosensing technologies for real-time detection. Develop and implement novel surface chemistries to improve sensor performance
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design and execute experiments using lung cancer and lung infection Organ Chips. Develop, optimize, and characterize human lung microphysiological models for translational studies. Analyze and interpret
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across the following research areas: Predictive machine learning Robust and stochastic optimization Learning-enabled control and reinforcement learning Power system operations, planning, and electricity
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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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). The project focuses on experimental design, optimization, and construction of entangled and/or squeezed states of light for a range of applications. The role also involves building and setting up various
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) participant, you will join a community of scientists and researchers in an effort to optimize collection methods and protocols for human biofluids. This project will be in support of the Air and Space