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Field
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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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will develop novel statistical and machine learning methods for any of the following: multi-omics data (such as bulk and large-scale single-cell RNA sequencing data, spatial transcriptomics, bulk and
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have expertise in working with animal disease models, single-cell and spatial RNA sequencing technology, and a solid understanding of the CNS immune landscape. Additionally, applicants should have at
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, statistics (including spatial statistics), and in mapping and visualization. The ideal candidate will also have demonstrated capabilities in research project management and the ability to communicate research
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conservation of marine and coastal ecosystems. The successful candidate will also require strong technical skills in terms of statistical and spatial analyses, and the ability to coordinate and manage large
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projects in computer vision research, with a particular emphasis on Spatial Intelligence, 3D Computer Vision, and 3D Generative AI. You should hold a relevant PhD/DPhil (or near completion*) in Computer
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conservation of marine and coastal ecosystems. The successful candidate will also require strong technical skills in terms of statistical and spatial analyses, and the ability to coordinate and manage large
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mechanical design Experience with beam shaping techniques (e.g., spatial light modulators, diffractive optical elements) Proficiency in programming languages like LabVIEW, Python, MATLAB, or C++, and
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, S., A. Chaderjian, and O. A. Saleh (2023). Spatial organization of phase-separated DNA droplets. Physical Review X 13, 031014 Wilken, S., Abraham, G. R., and O. A. Saleh (2024). Condensation and
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manipulation, viral gene therapy, pharmacological studies, gene editing, and physiological measurements of cardiac electrical and mechanical function at a variety of spatial scales from a single cell to whole