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School of Electrical and Electronic Engineering (EEE), helping to develop algorithms and systems for disaster mapping and climate change in collaboration with space industries and responding agencies
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theoretical computer science to develop algorithms and/or data structures, to further our understanding of what is possible in various computation models. The Research Associate/Research Fellow is also expected
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laboratories and testbeds for optical communications in Europe and maintains a complete library of optical communications digital signal processing algorithms. We are recruiting students in the field of digital
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optimizing these patterns based on the Gerchberg-Saxton algorithm, and then building out an optical setup to test whether these phase patterns can successfully turn a Gaussian beam into the arbitrary predicted
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(e.g. transcriptomics, metabolomics) Knowledge of machine learning/deep learning algorithms Knowledge of systems biology approaches (e.g. genome-scale modeling) Proficient with R, Python or MATLAB Modes
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regarding this requirement, please reach out to the Financial Aid Office. Knowledge of the various social media platforms and algorithms associated with each site Attending all games, community service events
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multiscale simulation methods for quantum mechanical properties of macromolecules, developing novel ways to combine quantum chemical methods and machine learning, developing quantum algorithms
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genetic knockouts in yeast and mammalian cell lines, and protein purification. Job Responsibilities: 35%: Computational algorithm development and data analysis 35%: Design and conduct experiments with yeast
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university/spinout environment. This is a unique opportunity to work at the forefront of applied research and innovation, helping translate novel control algorithms and hardware prototypes into real-world
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biology or related field Experience with omics data analysis (e.g. transcriptomics, metabolomics) Knowledge of machine learning/deep learning algorithms Knowledge of systems biology approaches (e.g. genome