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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | 6 days ago
algorithms for environmental predictions (e.g. Random Forests, Support Vector Machines, K-nearest neighbors), as well as unsupervised algorithms for clustering (e.g. K-means, DBSCAN) Experience in extracting
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Gene expression modulation CRISPR/Cas9 (including knock-out, knock-in, CRISPRa, CRISPRi, viral vector systems) Next-generation sequencing (RNA-, ATAC-, ChIP-Seq, CUT&RUN, Hi-C and others) Pulldown and
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at the Faculty of Mathematics at TUD. Tasks: generation of hyper uniform patterns (point, scalar and vector fields) application of topological data analysis tools such as persistent homology and graph statistics
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning