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in these diseases. The postdoctoral fellows will work on computational method development and data analysis for bulk and single-cell omics data from human patient samples. Individuals with a strong
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author) in the field of computational biophysics (molecular dynamics simulations and/or quantum chemistry). Any experience in development and application of AI/ML methods in tandem with modeling and
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position for 2 years) We are looking for an early career researcher interested in responsible use of large language models (LLMs) to facilitate and support qualitative research methods, particularly in
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efficient learning methods that can function under limited communication, computation, and energy constraints while ensuring privacy and security from adversarial manipulation. The project focuses
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advanced computational tools to dissect the role of alternative splicing in these diseases. The postdoctoral fellows will work on computational method development and data analysis for bulk and single-cell
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for microbiological research and antibacterial drug discovery. The work mostly comprises of using various microbiological methods (e.g. antibacterial susceptibility testing, biofilm assays), designing, developing and
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advanced computational tools to dissect the role of alternative splicing in these diseases. The postdoctoral fellows will work on computational method development and data analysis for bulk and single-cell
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studies (STS), philosophy of technology, and political philosophy, placing a strong emphasis on qualitative empirical research methods. Through an empirical-conceptual methodological framework, the project
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doctoral degree in demography, public health/epidemiology, statistical sociology, statistics, population genetics or other relevant field, have strong quantitative methods skills and an excellent command
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-realities theme (HI-3) including but not limited to: Virtual, mixed, and augmented reality technologies; Artificial intelligence (AI) methods for extending human perception; Spatial AI technologies