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Field
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PhD Scholarship Develop multimodal machine learning models to predict glioblastoma treatment outcomes using imaging and clinical data. Work with real-world data from John Hunter Hospital in a
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modelling predictions. Experience or a strong interest in scientific programming and machine-learning-assisted data analysis for materials modelling is an advantage. PhD Position 2 – Coarse-Grained and
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as well as published in leading subject and high-impact publications. The post-holder will have the opportunity to teach. Applicants should hold a PhD/DPhil in atmospheric physics, physics, data
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of visualisation, machine learning, and human-computer interaction under the joint supervision of both institutions. The position is shared by TU Wien and USTP and offers the opportunity to conduct research at both
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alloys for energy applications in harsh environments using additive manufacturing. This research involves integrating computational modeling, machine learning, and experimental investigations to design and
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome
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. Lead and conduct research projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data
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Norwegian University of Science and Technology (NTNU) for general criteria for the position. Desired qualifications Applicants should possess a basic understanding of key AI concepts (machine learning
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should hold a Master's degree in Computer Science, Artificial Intelligence, Computational Linguistics, Data Science, or a closely related field Solid background in machine learning and natural