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.) experience with statistical methods (Bayesian statistics, machine learning etc.) We offer Lund University is a public authority which means that employees get particular benefits, generous annual leave and an
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the backbone of contemporary machine learning, yet conventional training methods often overlook the rich problem geometry that, when properly exploited, can enhance performance. In this project, we will, e.g
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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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leadership skills A strong quantitative background, preferably in machine learning or (Geo) AI Good communication skills Very good oral and written English language skills An international position in
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that have occurred and through physical experiments or simulated evacuation experiments in a real environment. Recently, computer-generated elements or environments have also come to play a major role with
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data analysis, non-Gaussian modeling, spatial and temporal stochastic modeling, Bayesian methods, or modern machine learning. This expertise should be supported by publications in top-tier journals
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of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. More information about the total announced post-doctoral positions within in
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Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may
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and conducts research and teaching mainly in Electrical Engineering and Computer Technology. We are located on LTH's campus in northern Lund. The Division for Electromagnetics and Nanoelectronics has 10