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Field
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perturbation screens with high content molecular and imaging data to understand cellular and multi cellular combinatorial programs in cells and tissues in health and disease. You will join a highly collaborative
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Please apply online and attach your resume (including a list of two referees), and a separate cover letter that outlines how you meet the selection criteria below: Essential Selection Criteria: PhD in
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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 2 months ago
to Apply Please apply online and attach your resume (including a list of two referees), and a separate cover letter that outlines how you meet the selection criteria below: Essential Selection Criteria: PhD
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. fluorescence imaging, molecular biology, cell culture, immunohistochemical assays, circuit manipulations, mouse surgery or behavioral assays) and electrophysiological recording (in vivo extracellular recordings
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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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as a model organism complemented by in vitro biochemical systems. The insights gained from this well-controlled model will provide a foundation for understanding analogous processes in more complex
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responsible for data/image acquisition, analysis and interpretation and for using this information to design efficient heterogeneous photocatalytic processes. This will involve working on the synthesis and
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. The Digital and Computational Pathology Laboratory in PCS is seeking a talented and motivated postdoctoral fellow to develop cutting-edge methodologies in computer vision and AI to power whole slide image
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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
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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