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, a person in this position will be a key contributor to the design and implementation of algorithms, AI/ML models, and workflows to enable the discovery of valuable information in large volumes of data
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learning algorithms for a variety of predictive analytics research projects. Coordinates data collection, econometric analysis and provides quality assurance for research projects. Contributes to research
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. Optimizes the performance and scalability of AI/ML workloads through algorithmic and system-level improvements, including evaluation and tuning of CPU vs. GPU usage for cost-effectiveness. Monitors and
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responsibilities will span all stages of research, including collecting data in both tabular and spatial formats, developing algorithms that clean and organize data, conducting statistical analyses, running
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Donnat, the assistant will preprocess raw omics data, conduct exploratory and multivariate analyses (e.g., PCA, CCA), and iterate on new algorithms for mutant detection and pathway discovery. The role is
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responsible for teaching six courses over the academic year in introductory programming, algorithms, machine learning, or systems depending on the candidates’ qualifications and programmatic need. In
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research in computational biology, single-cell ‘omics-based and multimodal machine learning (ML), and, for the candidate with appropriate skills, quantum computing algorithms and software for applications in
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, Databases, etc.), Machine Learning, Theoretical Computer Science (Discrete Mathematics, Algorithms, etc.). Experience with EdTech tools, such as Ed Discussion, Gradescope, GitHub Classroom, Canvas, etc
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weather events and align closely with established physical climate principles and AI theory. Contribute to algorithm development and foundational model design for innovative AI weather and climate
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, validates and implements sophisticated algorithms for clinical processes in the transplant program and more broadly in the Section of Pediatric Hematology/Oncology & Stem Cell Transplantation. Coordinates