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Field
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Intelligence (AI) and machine learning, digital sociology, AI and the sociology of knowledge, AI and expertise, and digitalization and criminology (digital criminology). A prerequisite for employment is that
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on leveraging data from permanent forest plot datasets in the Caribbean to build a comprehensive view of tropical tree species in support of conservation and broader management actions. Learning Objectives
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Qualifications Work Experience: Experience with research involving animals. Animal Behavior training and testing. Single unit neurophysiology data acquisition and analysis. Skills: Highly motivated to learn
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methods Experience analysing RNAseq and/or high throughput imaging data Experience handling human post-mortem tissue Experience writing/using computer code Experience supervising postgraduate students and
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are included but clinical medical themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data
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-atomic potentials using a combination of classical and machine-learning (ML) approaches (and a new hybrid method recently developed in our group). Some of the types of simulations that will be performed
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machine learning techniques to enhance source detection sensitivity. Multimessenger modelling and interpretation of Galactic sources. This position offers the opportunity to work at the forefront
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power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods
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in several areas. These include, but are not limited to, Using MPS to identify new potential targets for future medical countermeasure development Learning development and characterization
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developing machine learning or data science approaches for patient stratification and genetic association analyses using cardiac magnetic resonance imaging in biobank populations. Successful applicants will