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Field
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the application of rock physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or
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model fitting, including Bayesian model fitting. Experience of management and analysis of large multidimensional real world data sets. What we can offer you The opportunity to continue your career at a
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, particularly NaTech (Natural Hazard Triggering Technological) events. REUNATECH is a Horizon Europe Marie Skłodowska-Curie Doctoral Network that aims to educate and train the new generation of Doctoral
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spatial mass spectrometry. Experience with single-cell omics is also an advantage. Advanced biostatistics and machine learning, such as multivariate analysis, regularization, deep learning, or network
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To participate in School research activities. To build and create networks both internally and externally to the university, to influence decisions, explore future research requirements, and share research ideas
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also be part of the MBIC Graduate School, which provides additional training and networking opportunities. Predictive processing is increasingly recognized as a key computational principle of brain
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- based neural networks, Bayesian statistics, and text analytics are a must. Nice to Have: Experience developing and integrating APIs for healthcare systems to ensure seamless interaction with AI models
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has been identified References: Comley, Joshua W. and D.L. Dowe (2003). General Bayesian Networks and Asymmetric Languages, Proc. 2nd Hawaii International Conference on Statistics and Related Fields, 5
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theoretical understanding of statistical machine learning methods relevant to the project: Bayesian learning, machine learning, spiking neural networks. Experience of programming (e.g. with Python) and data
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of identifying excellent researchers and accelerating them in using AI to advance and disrupt Science or Engineering. Here ‘AI’ is interpreted very broadly, e.g.: topics in Bayesian Inference and Robotics