31 parallel-processing-bioinformatics-"Multiple" Postdoctoral scholarships in Germany
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, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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of the project is to develop and apply bioinformatic tools for the analysis of high-dimensional immunological data sets. Our laboratory (Zielinski lab) focusses on human T cell regulation in health and disease. We
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Germany Web: https://www.mpinat.mpg.de/grubmueller Social Media: https://bsky.app/profile/compbiophys.bsky.social www.mpinat.mpg.de/ Information pursuant to Article 13 DSGVO on the collection and processing
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13.03.2023, Wissenschaftliches Personal We are looking for motivated students to work on the development and implementation of a cheap and scalable ceramic processing concept towards a fully sprayed
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graph processing frameworks, graph databases, graph learning frameworks, knowledge graph systems, and graph mining systems. While each of them is specialized on a specific type of task and is highly
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talented individuals passionate about AI, Human-Computer Interaction, Eye-Tracking, and their responsible applications. Ideal candidates will have: • An M.Sc. degree (or equivalent) in Computer Science, Game
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Engineering, Computer Engineering, Computer Science, or a closely related field Strong background in robotics fundamentals: kinematics, dynamics, control, planning Proficiency in programming (C++, Python), and
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University of Munich (TUM). Please view our privacy policy on collecting and processing personal data in the course of the application process pursuant to Art. 13 of the General Data Protection Regulation
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 1 month ago
skills and experience and interest in data analysis, data science, machine learning and process automation would be an advantage. Previous experience with XAS or other synchrotron-based techniques would be
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flow within cerebral aneurysms. Arterial geometries are derived from medical scans (e.g., CT) of real patients, which are suitably meshed and processed for numerical treatment using Lattice-Boltzmann