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-driven, quantitative analysis. The laboratory integrates large-scale methods such as transcriptomics, proteomics, metabolomics, and network biology to understand how viruses reshape host cell systems on a
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cell or intracranial electrophysiological recordings, prior publications using electrophysiological recordings, advanced analysis skills, or previous experience with assessing behavioral and neural
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models, and analysis of clinical trial and multi-omics datasets. Fellows are encouraged to publish in high-impact journals, contribute to intellectual property, and participate actively in international
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specializes in fluorescence and Raman-based approaches, integrating advanced microscopic analysis to gain molecular-level insights into complex materials and systems. The lab is internationally recognized
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, preferably using yeast Genome engineering / synthetic biology, yeast and/or mammalian Cell biology, microscopy, and biochemical approaches Functional genomics and computational data analysis, including AI
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responses, α-synuclein pathology Immunofluorescence and confocal microscopy, high-content imaging, quantitative image analysis, SDS-PAGE and Western blot Testing of candidate compounds Contribution to single
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and analysis of psychophysiological, e.g., ECG, photoplethysmography, behavioural, e.g., interoception, and self-report data, e.g., interoception, somatic symptoms, mental health, from different sources
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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of the research, contributing to protocol writing, and helping to oversee the execution of the research. The postdoctoral scholar will also contribute to data analysis and write-up of scientific findings
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at the intersection of machine learning, CRISPR screening data analysis, and multi-omics to uncover genetic interactions and synthetic lethalities in cancer. Develop and apply scalable, reproducible computational