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and uncover yet unknown physiological particularities of sleep and other human health factors. Your Profile PhD (or near completion) in Biomedical Engineering, Computer Engineering, Computer
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establish a research profile. Develop and execute innovative research projects. Develop, train, and evaluate modern machine-learning models on GPU/HPC infrastructure. Integrate AI methods with scientific
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Science in Earth Observation develops innovative signal processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth
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methods You will work closely with: - Dr. Martin Ramacher (machine learning for environmental applications) - Dr. Matthias Karl (urban air quality modelling and emissions) and collaborate within a project
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 2 months ago
methods or machine learning is an advantage # Strong communication skills and a collaborative approach to working with internal and external partners # Independent, structured and solution-oriented way
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position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description:Postdoctoral Researcher - Machine Learning for Plant Regulatory Genomics
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, for event reconstruction and classification, including potentially machine learning/AI Interpretation in suitable theoretical models Contribution to software activities that are required for wider use by DESY
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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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-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