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-driven research group working at the intersection of computational genomics, clinical artificial intelligence, and imaging genetics. This position offers an exciting opportunity to develop novel algorithms
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. The student will support research activities including implementing and testing algorithms, conducting experiments, reviewing technical literature, analyzing results, and assisting with research publications
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ensuring that the data are of high quality, and running algorithms to identify genomic alterations. The goal of this research is to result in a published manuscript. Basic Qualifications BS in computational
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programs in Algorithms, Combinatorics, and Optimization (ACO), Computational Science and Engineering (CSE), Bioinformatics, Quantitative Bioscience (QBioS), and Machine Learning (ML@GT). Equal Employment
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open to generate a pool of qualified student applicants for available positions during the semester. Tutor students in computer science courses, including programming, algorithms, data structures, and
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. They are key players in several cross-disciplinary institutes, centers, and programs at Georgia Tech, including PhD programs in Algorithms, Combinatorics, and Optimization (ACO), Computational Science and
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to candidates with teaching or research interests in: Algorithms Science of Programming Computer Vision Machine Learning Qualifications Applicants must have: A Ph.D. in Computer Science, Data Science, Artificial
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ensuring that the data are of high quality and running algorithms to identify genomic alterations. The goal of this research is to result in a published manuscript. Basic Qualifications BS in computational
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implications of artificial intelligence, algorithms, digital platforms, or other emerging technologies. Such research may advance data science methods, deepen our understanding of economic effects of new methods
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 1 month ago
preserved at ambient temperature provided it is protected from light and humidity. Goal The goal of the project is to develop an algorithm to allow robust retrieval of data in the context of DNA-based data