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Field
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. Coordinate modelling activities across multiple projects and deliver high-quality outputs on time. Integrate new methodologies, including AI and machine-learning approaches, into simulation design. Conduct
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protein coding genetic association data with functional and machine learning-derived features 4. Developing methods to characterize the genetic architecture of autism Salary and Benefits This position is
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, computational social science, and/or machine learning applications. Acquisition, processing, and analysis of remote sensing imagery. Proficiency with GIS methods, applications, and visualization. Prior experience
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strong sense of community & inclusion Enjoy a career that makes a difference by collaborating & learning from the best At UNSW, we pride ourselves on being a workplace where the best people come to do
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-Coding Genome Edits: Develop innovative machine learning approaches for designing precise non-coding genome edits, focusing on how non-coding alterations influence gene regulation and cellular function
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mathematics, computer science, electrical engineering, machine learning, optimization, statistics, etc.) and specific domain area. Finalists will be paired with mentors by the search committee, facilitating a
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bring expertise in computational methods (such as machine learning, chemo-informatics, molecular dynamics simulation, structural biology) and / or experimental methods (such as biophysical analysis
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. This project involves the development and application of interpretable machine learning methods to uncover allosteric regulation of disordered regions in the dynamics of G-protein coupled receptors to enable
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for analysis (e.g., text manipulation); · One or more computational environments for statistical analysis (e.g., MATLAB, R, or Stata); · Creating and managing very large datasets; · Machine
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to the project’s scope, such as mechanistic interpretability of LLMs, robustness verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research