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in developing and implementing project ideas. Is motivated to invest the effort required to publish in leading academic journals. Has excellent training in statistics and quantitative methods with
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experience with modern deep learning frameworks Solid understanding of applied statistics Experience working with large-scale image datasets Excellent English communication skills Desirable qualifications
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of Chemistry, and the group of Prof. Hobolth at the Department of Mathematics. A second postdoc with expertise in stochastic processes and statistical methods will be part of the project and you are expected
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and statistical tools to identify patterns in large datasets The candidates should demonstrate evidence of self-driven and independent research capability, excellent collaboration and communication
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(programming, digital signal processing, modelling, statistics) is sought. The project involves collaboration with Prof. Marco Steinhauser (University of Eichstätt-Ingolstadt, Germany) and Dr. Ramakrishna
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vision and strong analytic and quantitative skills (programming, digital signal processing, statistics) is sought. Qualifications Ideally, applicants for the position should satisfy the following
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of Chemistry, and the group of Prof. Hobolth at the Department of Mathematics. A second postdoc with expertise in stochastic processes and statistical methods will be part of the project and you are expected
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, supported by a good understanding of urban water systems, water quality, environmental chemistry and statistics. You should have experience in the development and application of water quality models, with
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engineering, data science, statistics, mathematics, physics or an adjacent subject, with focus on medical image analysis and/or deep learning. Furthermore, the following competences will be expected
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, establish their statistical properties, and evaluate performance on both simulated and empirical data. Beyond advancing econometric theory, the project aims to deliver practical tools for applied researchers