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Apply Now Responsibilities* Conduct research focused on designing and implementing algorithms related to cryo-electron microscopy (cryo-EM) data collection in a lab that focuses on the structural
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multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and their dynamics. Conducting literature searches, manuscript preparation, and
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within the MPOG registry. MPOG utilizes clinical phenotypes to identify cases for inclusion in research or quality improvement initiatives. Phenotypes are coded building blocks or algorithms used to sort
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. Learn, utilize, and maintain Charge Master data in FinThrive and in the Epic EAP master file. Set hospital rates following department policy, using standardized pricing algorithms, available benchmarking
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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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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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and intermediate level, with a focus on programming control, perception, planning, and algorithmic functions for robots. Topics will include data representation, memory concepts, debugging, recursion
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Medicine and Bioinformatics. The specific objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms
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or improvement. The intern will analyze the performance of AI models by comparing model predictions against established benchmarks. They will contribute insights on how to optimize algorithms and improve
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the original audio tape. This process of verification occurs before the written text is used to train our augmented intelligence coding algorithms. De-identified transcripts and audio tapes will be accessed