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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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, 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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-based methodologies for protein structure prediction and cofolding Machine learning guided virtual screening Taking on organizational tasks and writing grant applications Your Profile The ideal
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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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clinical trials in allogeneic hematopoietic stem cell transplantation and CAR-T cell therapy. Through close integration of laboratory and clinical research, we aim to translate mechanistic discoveries
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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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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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scattering for structure and dynamics of these systems. For more information, see https://www.soft-matter.uni-tuebingen.de . Currently we are looking for a post-doctoral researcher to perform state-of-art X
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, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100