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on the development of Bayesian statistical/machine learning methods for the data integration analysis of high-throughput imaging and molecular data (i.e., genome, transcriptome, epigenome, and more). The methods would
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presentations and posters. 5% Mentoring Training graduate, undergraduate and technical staff in theoretical and/or bench science Qualifications Required Qualifications: PhD in Biochemistry, molecular biology or a
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-photon imaging in the ferret. The end goal of our work is to test a model of excitatory-inhibitory interactions against data collected in an animal model with columnar architecture in primary visual cortex
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disease which combines behavioral and genetic models, metabolic, neuroendocrine and imaging techniques in living animals as well as sophisticated molecular and structural biology analyses of neuropeptides
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secondary electron detector for surface imaging at the atomic scale, and hybrid-pixel detector for 4D-STEM. The second STEM will be an ultra-high vacuum environmental STEM with nine orders of magnitude
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documented on application materials. Required Qualifications: • PhD, MD, or equivalent. • Experience collaborating with clinical and research faculty in an academic setting. • Excellent spoken and written
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reconstruction approaches that provide increased SNR and image acceleration. The proposed work will also involve data analysis through novel image processing and analysis tools developed within the HCP. Ideal
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materials. It will have a secondary electron detector for surface imaging at the atomic scale, and hybrid-pixel detector for 4D-STEM. The second STEM will be an ultra-high vacuum environmental STEM with nine
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-applicable to candidates who have been awarded a PhD) p.a., plus 17% employer's superannuation and annual leave loading - Appointment Type: Fixed Term employment for 12 months (with possible extension
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Hartvig Clausen (DTU) and U Copenhagen scientists Dr. Céline Galvagnion, Prof. Nikos Hatzakis, Prof. Martin Lauritzen and Dr. Krzysztof Kucharz. Work includes purification and biophysical analysis