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(link ). Our expertise comprises various aspects of quantum computing, from quantum chemistry and optimization to machine learning (ML). With our activities in quantum-assisted optimization, we
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Max Planck Institute of Immunobiology and Epigenetics, Freiburg | Freiburg im Breisgau, Baden W rttemberg | Germany | 3 months ago
of high-throughput sequencing data, including RNA-seq, ChIP-seq, ATAC-seq, and single-cell and spatial omics. Integrate machine learning and large language models (LLMs) into bioinformatics workflows
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its detailed analysis through Oxford Nanopore Technologies (ONT). Your role will be central in creating and applying bioinformatics and machine learning tools to analyze long-read data and decipher cap
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organised, accurate in their experimentation and adaptable to learning new techniques. Primaryresponsibilities Preparation and processing of animal histological samples, including organ embedding, cutting and
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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statistics, bioinformatics, machine learning and AI applications. Experience in a number of these technologies is expected. Collaborations within the Cluster of Excellence ImmunoSensation and with other intra
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interdisciplinary research, integrating molecular simulations, machine learning, statistical physics, multiscale modeling, and uncertainty quantification. By integrating state-of-the-art machine learning models
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
apply machine learning/AI methods for ecological analyses Expedition experience Further Information The AWI is characterized by The AWI is characterized by our scientific success - excellent research
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of methodologies, from in-depth behavioral assessments to computer vision, machine learning and neuroimaging techniques, we aim to uncover the complexites of neurodevelopmental disorders. Our
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with other research groups for chip applications, e.g. in physics, life sciences, materials sciences, medicine, and machine learning. Chip Design is also a focus of the Master′s program in Computer