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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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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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, 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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(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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theory, physics, mathematics, computer science, and statistics. This Postdoc position falls under Research Thrust RT4 on Reliability and Trustworthiness. The objective is to explore and address research
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, mathematics, computer science, and statistics. This Postdoc position falls under Research Thrust RT4 on Reliability and Trustworthiness. The objective is to explore and address research and design challenges
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management Solid knowledge of statistical methods as applied to sensory testing and consumer research; experience with key software such as XLSTAT, R, SPSS or similar Multivariate data analysis skills (sensory
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genetics Experience with receptors/receptor signalling is an advantage Experience in omics data handling and statistical analysis Excellent written and spoken English communication skills Experience with
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and verbal English communication skills Candidates with backgrounds in Physics, Mathematics, or Statistics are also encouraged to apply if they have strong competencies relevant to machine learning