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computational analysis, provide the summary reports of results, and contribute to grant and manuscript writing. Salary and Benefits This position is salaried and benefits eligible. Information regarding
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synergy with its strategic partners, and provide training on causal inference to the next generation of investigators. For more information on CAUSALab, please visit: https://causalab.sph.harvard.edu
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, epigenomics, nucleomics, etc.) Multimodal spatial and single-cell data visualization 2D and 3D bioimaging data visualization Data analysis and data management infrastructure for biomedical data visualization
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for: Analysis of bulk and single cell RNA-sequencing, spatial transcriptomics, and proteomics datasets Integration of experimental model data with public and clinical datasets Statistical modeling and survival
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, covering areas such as LLMs, generative AI models, computational biology, and the analysis of high-dimensional neural and behavioral data. The Fellowship is intended for early-stage scientists and will
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studies, and how information about benefits, harms, and uncertainty is communicated to clinicians, patients, and payers. We welcome applications from recent PhD graduates and postdoctoral fellows who
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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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on understanding the earliest stages of high-grade serous ovarian cancer (HGSOC) by integrating spatial multi-omic profiling with computational analysis to define how precancerous lesions evolve into invasive
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(preferably infant or toddler) data Strong written and oral communication skills Strong analysis and programming skills (preferably in R and/or python) Ability to work independently and as part of a team
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research design and data analysis, including any of the following: clinical trials, implementation science, economic evaluation, digital health, statistical analysis for clinical trials, or big data analysis