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: Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including bioengineering, computer science, statistics, or mathematics. Strong
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-new lab that previously made important contributions to the development of novel predictive computational tools in single cell and spatial transcriptomics. Representative publications include
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Postdoctoral Associate Required Qualification: (as evidenced by an attached resume) PhD or foreign equivalent degree in hand by August 2025. Preferred Qualification: PhD or MD in Biomedical
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Postdoctoral Associate Required Qualification: (as evidenced by an attached resume) PhD or foreign equivalent degree in hand by August 2025. Preferred Qualification: PhD or MD in Biomedical
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of the rich and varied training and career development opportunities offered at HSPH. Basic Qualifications · PhD or equivalent in computational biology, computer science, epidemiology, statistics, mathematics
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, and spatial transcriptomics. Key responsibilities include: Developing AI/ML methods for image alignment across modalities Automated feature detection Predictive modeling of vascularization patterns
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on developing machine-learning-based or statistical emulators to approximate key outputs of complex Earth System Models, with the aim of enabling efficient uncertainty quantification, sensitivity analysis, and
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. We are seeking an energetic and independent researcher who has a strong background in quantitative analysis of social surveys. To qualify for the position, a candidate must have completed a PhD by the
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based on single-cell and spatial omics data, and (iii) integrating regulatory profiles with multi-modal data. These efforts aim to uncover regulatory mechanisms behind cancer and to develop predictive
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single-cell and spatial multi-omics datasets. The primary focus of this role is to delve deeper into the molecular mechanisms driving intra-tumor heterogeneity, plasticity, and therapy resistance