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computational methods and tools, including prior experience with algorithms relevant to computational biology, is a plus. ● Ability to work independently as well as part of an interdisciplinary team in a
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modeling and AI. This position will include: Developing new Generative AI algorithms for developing intelligent agents in areas such as planning, exploration, perception, physical reasoning, and memory
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bioinformatics analysis pipelines for processing RNA-seq, single-cell RNA-seq, genomics and proteomics data. Develop novel algorithms and integrated data visualization applications when existing software packages
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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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differentially private learning, its connections to replicability of algorithms, and algorithmic fairness. Basic Qualifications Candidates are required to have a doctorate or terminal degree in Computer Science
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of detailed protocols including operational definitions, data dictionaries and ICD/CPT codes used for algorithms; will be responsible for making statistical analyses code publicly available on GitHub ensuring
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research team. Key research areas include: Development of low-carbon materials and tunable thermal energy storage materials integrated with smart sensors and advanced algorithms Creation of Digital Twins
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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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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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is interested in understanding the neural and algorithmic basis of sensory-guided behaviors in terrestrial animals. We have developed behavioral tasks in mice using stimuli and situations