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Details Title Postdoctoral research fellows in generative, multimodal AI, and seismic foundational models School Faculty of Arts and Sciences Department/Area Earth and Planetary Sciences Position
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of machine learning models for object detection, classification, and outlier detection across multiple sensor modalities. Depending on previous experience, provide scientific oversight to volunteers, students
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, single-atom catalysts), analytical instrumentation (including electronics and LabVIEW FPGA programming), finite element modelling using COMSOL Multiphysics, and in-situ/operando spectroscopy, among other
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the pseudostratified architecture found in epithelial tissues, and how the architecture is exploited for various functions such as morphogenesis, organ development, and tissue fate. We use diverse model organisms
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inaccessible regimes. Work in the lab combines optics, protein engineering, chemistry, electrophysiology, simulation, and theory. We work at the levels of individual molecules, single cells, and whole
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deal of independence, can choose their research topics, and work with multiple faculty members. Candidates for this position must have completed their Ph.D. degree by the appointment start date
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the direct supervision of a postdoctoral fellow to study breast cancer initiation and progression using a newly developed mouse model of breast cancer together with primary patient samples. You will
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computational and systems biology approaches to analysis of single-cell RNA-sequencing data. These datasets derive from samples of human lungs, and also from mouse models of airway injury, inflammation and
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Qualifications Preference will be given to candidates with prior experience in one or more of the following areas: ecological (population) modeling, geographic information science, remote sensing, population
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, single-atom catalysts), analytical instrumentation (including electronics and LabVIEW FPGA programming), finite element modelling using COMSOL Multiphysics, and in-situ/operando spectroscopy, among other