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Field
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management and analysis: Collect, manage, and analyze experimental data using statistical and modeling tools. Interpret results to draw meaningful conclusions and develop recommendations for sustainable
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-performance computing, machine learning models (eg. LLM), probabilistic models for data, novel techniques for making measurements, visualization tools, and community-oriented foundational software tools. Please
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PhD (or near to completion) in relevant subject area (structural biology or biophysics) High level analytical capability Ability to communicate complex information clearly Fluency in relevant models
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new models of examining the data To provide teaching to junior staff in the lab in neuroscience-related research methods, especially in pre-processing and processing of EEG data from infants/children
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Python and R for use in data science and modeling. Excellent writing and communication skills; demonstrated publication record. Preferred Qualifications Knowledge of cancer biology, clinical oncology
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Type: Salary Compensation Statement: The pay range listed for this position is determined by our compensation program using market data and salary benchmarking. A combination of factors is considered in
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genetics of disease models, human pluripotent stem cells derived neurons, high content imaging, electrophysiology, single cell RNA sequencing, bioinformatics, and spatial transcriptomics technologies. We
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interest and experience The responses against the Selection Criteria^ (found in the Position Description) ^For information to help you with compiling short statements to answer the selection criteria and
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responsibilities of the position include: - Conduct cutting-edge research at the intersection of AI and scientific discovery, focusing on identifying spatiotemporal motifs in complex biological cells and bio
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contribute to the collaborative TQT research community. Please visit the University of Waterloo website for more information on Postdoctoral positions. Principal Investigator: Subha Kalyaanamoorthy Project