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models, and efficient algorithms for large-scale genomic data analysis. This is a one-year appointment starting as early as possible, with renewal possible based on the availability of funds, availability
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RNA-seq, genomics and proteomics data. Develop novel algorithms and integrated data visualization applications when existing software packages are not available or are not adequate. 2.) Apply
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by applying existing and novel computational biology, bioinformatic, and machine learning algorithms to sequencing datasets and correlating them with multi-dimensional clinical datasets that contain
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, the Postdoctoral Researcher will drive research at the intersection of health data science, multimodal AI, digital twins, computational phenotyping, and responsible AI. PhD must have been received within the last
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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive
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algorithms to enable autonomous execution of surgical interventions. The research program will include a systematic investigation comparing this autonomous surgical paradigm against expert surgeons performing
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University): Quantum Computation & Quantum Algorithms https://youngseok-kim1.github.io/ykim.github.io/ 3. RESEARCH AREAS [Condensed Matter Physics] - Quantum topology and geometry - Topological materials
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-Informed Neural Networks (PINNs) and hybrid models that respect the physical laws governing the real-world system Applying Deep Reinforcement Learning (DRL) algorithms to optimize processes within simulation
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include: Lead original research in multimodal and causal AI for health; design, implement, and rigorously evaluate algorithms and full pipelines. Build reproducible research pipelines and maintain reliable
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progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and