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sensor data) mentioned. * Experience with multi-omics data analysis (e.g., genomics, transcriptomics, proteomics). * Familiarity with neuroimaging data analysis tools (e.g., FSL, SPM, or FreeSurfer
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. clinical data, imaging data, genomic and omics data, device and sensor data) mentioned. ● Experience with multi-omics data analysis (e.g., genomics, transcriptomics, proteomics). ● Familiarity with
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of digital technologies for individuals with mental illness. These technologies may include algorithms, wearable sensors, and apps for digital phenotyping, ecologically valid assessment (e.g., cognition
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intelligence and machine learning, with a focus on applications in library and information science. The AI Research Scientist will design and implement novel AI algorithms and models to enhance and expand
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in histology and molecular biology techniques. Experience with IACUC and institutional protocols. Experience with transcriptomic bioinformatics analysis (Seurat, Scenic algorithms on 10x Genomics
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molecular biology techniques. Experience with IACUC and institutional protocols. Experience with transcriptomic bioinformatics analysis (Seurat, Scenic algorithms on 10x Genomics databases). Experience with
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in histology and molecular biology techniques. Experience with IACUC and institutional protocols. Experience with transcriptomic bioinformatics analysis (Seurat, Scenic algorithms on 10x Genomics
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programming (e.g., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication
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., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication-efficient and
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programming (e.g., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication