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Field
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Research Back Profile Areas Cluster of Excellence CMFI Cluster of Excellence GreenRobust Cluster of Excellence HUMAN ORIGINS Cluster of Excellence iFIT Cluster of Excellence Machine Learning Cluster
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cutting-edge big/deep data analysis methods, including machine learning and artificial intelligence. The ideal candidate will therefore have a strong background in data science and in the application and
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Biology, Computer Science or related studies) Experience in Python with PyTorch (or equivalent) programming Experience in sequencing data analysis Basic knowledge in machine learning Experience with linux
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and concise summaries of scientific papers that capture the essence of the research. Identify and classify major conferences and events on quantum computing, quantum machine learning and quantum
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Research Back Profile Areas Cluster of Excellence CMFI Cluster of Excellence GreenRobust Cluster of Excellence HUMAN ORIGINS Cluster of Excellence iFIT Cluster of Excellence Machine Learning Cluster
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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multimodal datasets Design and fine-tune machine learning and deep learning models to extract meaningful patterns and predict metastatic behavior Collaborate closely with experimentalists for mechanistic
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such as ecology, economy and social sciences. ZMT aims to use data science tools, including computer vision and deep learning, for the study of rapid changes in tropical coastal socioecological systems
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maintain pipelines for the analysis 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