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. The candidate will be expected to work in a team setting with other research staff and PhD students supporting the Project HOPE 1000 pregnancy cohort. The candidate will be expected to conduct independent
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cancer models and patient-centered translational approaches to define mechanisms that regulate treatment response, immune evasion, and disease progression. Candidates with experience in cancer biology
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. The successful applicant will possess a PhD or equivalent doctoral degree in the social sciences, including political science, public policy, political ecology, law, geography or another relevant field with some
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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell
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-edge technologies, including genetically engineered mouse models, patient-derived models, single-cell and spatial genomics, organoid systems, and preclinical therapeutic studies. Learn more about our
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and anticipated conferral date. Experience working with rodent models of pain, inflammation, neuroscience, or related biomedical research. Demonstrated ability to independently design, execute, analyze
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proteostasis, cytoskeletal dynamics, and ferroptotic cell death. This collaborative work combines biochemistry, chemical biology, cell signaling, live-cell imaging, and organotypic brain slice models to dissect
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neurobiology, RNA biology, and evolution. We are especially interested in understanding: How does post-transcriptional control shape neural cell fate and disease? We have discovered canonical and non-canonical
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, and apply Crainbow mouse models that express multiple HER2 isoforms — wild-type (WT), D16, and p95 which are essential reagents for the laboratory’s DoD funded program. Minimum Requirements: Ph.D
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in AI for genomics (e.g., generative models, transformers, genomic language models, agentic AI) and related areas of statistics (e.g., uncertainty quantification for machine learning and AI). Apply