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Field
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hands-on experience with advanced techniques, including patch clamp, optogenetics, fluorescence imaging, auditory brainstem response (ABR), stereotaxic surgery, RNA-seq, and computational modeling
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candidates] Design and develop prototype and testbed systems that will be deployed to community partners and stakeholders. All candidates will be expected to support the evaluation and assessment of deployed
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University of California, Los Angeles | Los Angeles, California | United States | about 22 hours ago
learning process throughout the year. The trainees also interact in a more limited fashion with the other residents and fellows in our Pathology Department via joint conferences and clinical interactions
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generating data utilizing advanced instrumentation/techniques, flow cytometry, confocal imaging, live animal IVIS and CT-PET machines, X-ray radiation, XCELLigence, Seahorse, ultracentrifuge, Proteomics (Mass
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strategies that modulate the crosstalk between tumor and immune cells, and develop new image-based screening technologies to identify targets that mediate clinically-relevant cell-cell interactions
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years of research experience in biology or a related discipline. Publication record demonstrating computational skills in image processing or genomic data analysis. Proficiency in rodent neurosurgeries
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image processing (e.g., in Matlab), and Fourier optics are desirable. Knowledge of visual optics is not required, though beneficial. The project is supported by federal funding. Rank and salary will be
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techniques include motor/behavioral tests of mice, in vivo compound administration, postmortem tissue harvesting and processing with a focus on the nervous system, cell tracing, immunohistochemistry, mouse
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and budgets. Engaging with the wider context Enhancing your contribution to the organisation through an understanding of the bigger picture and showing commitment to organisational values. Developing
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML