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Field
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main project by addressing specific case studies or specific targeted techniques. The main tools to be used will come from the discipline of Machine Learning, particularly those based on Bayesian methods
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prevalent is polygraph testing which infers deception through the measurement and analysis of physiological responses (e.g., blood pressure, electrodermal activity). However, despite its widespread
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, perform cutting-edge analytical techniques for causal inference and prediction, and writing papers for both an academic audience and for practitioners (managers and/or policymakers). Desired Qualifications
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enable the model to infer health-related information directly from NMR spectra of human blood. To this end, the model will be pre-trained using self-supervised learning on large-scale, partly synthetic
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). The goals are to develop new computational methods that allow the scientific inference of explainable attributes to describe human behavior and self-reports as well as to make progress in the computational
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populations from New Guinea using museomic data Assembling high-quality reference genomes and generating whole-genome resequencing data of avian skins Inference of evolutionary history using Ancestral
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Research Assistant/Associate Professor (Proteomics and Bioinformatics), Non-Tenure Track - (220000I3) POSITION SUMMARY Location: On-site at the University of Maryland School of Pharmacy, Baltimore
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in progress). In exceptional cases, candidates with an outstanding bachelor's degree alone may be considered. Demonstrated competence in causal inference methodologies and econometric identification
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to reason about software (e.g., LLM agents for finding and fixing bugs) Static and dynamic program analysis (e.g., to infer specifications) Test input generation (e.g., to compare the behavior of old and new
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to reason about software (e.g., LLM agents for finding and fixing bugs)Static and dynamic program analysis (e.g., to infer specifications)Test input generation (e.g., to compare the behavior of old and new