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models to study semantic relationships and changes in language during different periods of conflict collaboration with an interdisciplinary team performing statistical analyses active role in writing
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-omics liquid biopsy data for minimal residual disease (MRD) detection, quantification, and assessment. This project will involve applying and evaluating statistical and machine learning models for data
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Title: Disentangling and modelling behaviourally-relevant visual and semantic dimensions of visual cognition in the human brain (Kamila Maria Jozwik lab, the University of Cambridge)Application
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Description Completion of doctoral thesis related to: Process and analyze experimental data. Develop predictive models using deep learning. Train, validate, and optimize neural networks (CNNs, etc.) applied
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to: -Identification and analysis of existing quality evaluation frameworks and models for the assessment of interlingual live captions, including the most frequent workflows used and in varied language pairs (EN-ES, EN
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complex, high dimensional and high-volume datasets. Uses data preparation, modeling and predictive modeling, analysis, processing, algorithms, and systems. Applies knowledge of statistics, machine learning
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mathematical modelling are encouraged to apply. Terms of employment include competitive salary and benefits. Research in the SIT-D lab focuses on understanding and modelling consumers' behavior and decision
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Biotechnology and Bioprocesses, Membrane Technology, Chemicals and Materials, Resource Recovery, and Modelling & Artificial Intelligence. By harnessing its cross-cutting, interdisciplinary, and transformative
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studying vascular biology, pancreas physiology or diabetes • Knowledge and Experience with programming, signal processing, or numerical modelling • Knowledge and Experience working with rodent animal
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, knowledge, abilities, education, licensure and certifications, and other business considerations. Salary offers at the top of the range are not common. Visit UC Benefit package to discover benefits