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mechanisms understanding and optimize treatment for mental health using computational tools, with a particular focus on developing ecologically valid computational frameworks and models. Our research uses both
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interpretation of key effectiveness and implementation outcomes. • Apply implementation science frameworks to guide selection of measures, analytic plans, and interpretation of implementation determinants and
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implementation science frameworks to guide selection of measures, analytic plans, and interpretation of implementation determinants and outcomes. • Support or lead “big data” analyses
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within a multidisciplinary team Preferred qualifications Experience with longitudinal or hierarchical modeling frameworks Familiarity with transdiagnostic or dimensional approaches to psychopathology (e.g
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to refine mechanisms understanding and optimize treatment for mental health using computational tools, with a particular focus on developing ecologically valid computational frameworks and models. Our
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framework for unsupervised deep imaging phenotyping and imaging GWAS. The lab is now expanding these programs across pangenome informatics, clinical deployment-oriented AI, and multimodal imaging genetics
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data such as scRNA-seq, scATAC-seq, NGS, WGS/WES, GWAS, etc. Apply statistical genetics analysis frameworks such as LDSC, p-HESS, eQTL, QTL-GWAS, Mendelian randomization, statistical colocalization, etc
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resilience for mental health outcomes. This is an opportunity for scientists who want to do more than apply established tools to familiar questions. The lab is interested in building a deeper framework for
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integrates approaches across disciplines through common mathematical, statistical, and computational frameworks. WTI fosters a welcoming environment that provides equal opportunity to people of a broad range
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resource management frameworks. 2. Exceptional communication skills with the proven ability to translate complex cultural, legal, and ecological data into actionable strategies for philanthropy and