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Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | 3 months ago
. Experience in machine learning algorithms and tools. Experience in microscopy and image analysis. Effective collaboration in interdisciplinary teams. Strong analytical reasoning and persistence in experimental
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spatial omics data and to uncover the regulatory mechanisms driving cellular differentiation during vertebrate embryonic development. In this project, you will develop quantitative machine learning models
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Computer Science or Mathematics, ideally with a background in one or more of the following areas: Optimization, Game Theory, Machine Learning Applicants must demonstrate: • An excellent academic record, including
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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Hamburg, ESRF in Grenoble and others) analysis of the experimental data, ideally connecting to our machine learning tools presentation of scientific results on conferences and in publications supervision
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subjects, high interdisciplinary desire to learn, and willingness to cooperate, openness for internationalization and diversity, very good verbal and written English communication skills (good command
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, organization, compression, analysis, and visualization of georeferenced or geometric data in large scales. We put emphasis on methods of distributed computing, machine learning, image and text analysis