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institution of the Leibniz Association that combines methods of biomolecular basic research with analysis methods of bioinformatics and analytical high-performance technologies to investigate the complex
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the research landscape of Göttingen. The excellent biological, ecosystemic, environmental and mathematical research in Göttingen is reflected in this PhD programme. Sub-programmes: bioinformatics (computational
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transplantation and inflammatory diseases. We have scRNAseq data sets from 10x Genomics available and need you for data analysis using already implemented bioinformatic pipelines. This project is part of our ERC
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imaging and analysis methods together with an interdisciplinary team of physicists and structural biologists. Your Profile: Master degree in biophysics, bioinformatics, molecular or cell biology or related
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Max Planck Institute for Heart and Lung Research • | Bad Nauheim, Hessen | Germany | about 8 hours ago
, biochemistry, bioinformatics or related disciplines Language requirements TOEFL is not mandatory, but it will enhance your application. We also accept IELTS and other English certificates. Application deadline
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Retreats, guest lectures, symposia, and social activities Language of instruction: English Admission Requirements An above-average MSc degree in biological sciences or equivalent (e.g., bioinformatics) Proof
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and bioinformatics tools to study protein dynamics at the level of translation, degradation and import into organelles (Klann et al. Mol Cell 2020, Nature 2020, Schäfer et al. Mol Cell 2022, Delaunay et
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-learning algorithms Versatile data-science knowledge, including image and DNA sequences processing Programming skills in Python or other modern programming languages supporting AI and bioinformatics
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-08187-1 Your Profile: Master and PhD in biology, genomics or bioinformatics Strong background in data science or machine learning (deep learning, statistical modeling, or large-scale data analysis a plus
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Biomedical Research School (HBRS). BIOMEDAS is directed to students who are interested in combining disciplinary knowledge with the skills of a data scientist and working at the interface of bioinformatics