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Computational Systems Biology and Bioinformatics. The research will involve algorithm development and computational analysis of biomolecular information, using both traditional and newly developed methods
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teams to develop or improve algorithms for the analysis of cell regulatory and signaling networks; use models to predict how the genomic and epigenomic diversity affect physiologic or pathologic
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to develop or improve algorithms for the analysis of cell regulatory and signaling networks; use models to predict how the genomic and epigenomic diversity affect physiologic or pathologic phenotypes; and
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; development and review of periods of enrollment and term budgets; construction of algorithms, packaging formulas, rules, and other tools; creation and approval of selection sets; and batch posting data. Updates
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) disseminate results through quality publications and open-source algorithms and software. Qualifications: Ph.D. in Computer Science/Engineering, Biomedical or Electronic Engineering, Data Science, Biostatistics
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involves a deep dive into biological systems using computational techniques. The candidate will help design and implement algorithms to analyze complex biological data (like high-throughput sequencing data
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. Responsibilities Analysis of activations maps in mouse brains, primarily using R free-source library. Develop computer codes, primarily using ImageJ and Python, to implement algorithms for characterizing brain maps
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-physiology and the development and application of remote sensing algorithms is highly essential. The candidate should be proficient in working with data from a range of satellite sensors, with particular
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on the use of Machine Learning algorithms for rapid damage assessment. Research topics could focus on: the definition and use of novel damage sensitive features, physics informed machine learning, transfer