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Engineering, Computer Science or related + 2 years of experience researching multi-armed bandit problems and developing and analyzing Bayesian optimization and reinforcement learning algorithms + at least 3
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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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computational tools and algorithms developed in the lab for processing and visualizing proteomics data (known as FragPipe computational platform). The individual will work in close collaboration with other
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, including Ph.D. students and post-doctoral research fellows, and will have opportunities to contribute to new algorithm developments. Applicants should possess a Master's degree or higher in Bioinformatics
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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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designs and methods, clinical trial methods, Bayesian methods, and developing R packages and scalable algorithms. Opportunities for collaboration across the Department of Biostatistics and the Medical
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* Conduct a literature review on algorithmic bias and its impact on marginalized communities. Create an annotated bibliography and develop a structured research paper outline. Draft key sections
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. Provide accurate and timely follow-up with staff, patients and families. Process accurate and timely admissions as requested. Patient placement in accordance with placement guidelines, fill algorithms and
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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
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control strategies. Develop and implement advanced control algorithms for real-time operation and performance enhancement of power electronic converters and transformer-based solutions. Perform hardware-in