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for emulating high-resolution process-based land-surface models - Combine process-based land surface and vegetation model components with data-driven model parts, e.g. in the framework of Neural Differential
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at andreas.mulch(at)senckenberg.de For data protection information on the processing of personal data as part of the application and selection process, please refer to the privacy policy on our homepage at https
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candidates with disabilities will be given preference in the hiring process. The University of Tübingen is committed to increasing the percentage of women in research and teaching and thus encourages women
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to improve chimeric antigen receptor (CAR) T cell therapies by targeting genes and gene-regulatory processes to prevent CAR T cell dysfunction. Your tasks include but are not limited to: CAR T cell design and
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, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100
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at Thomas.Hickler(at)Senckenberg.de For data protection information on the processing of personal data as part of the application and selection process, please refer to the privacy policy on our homepage at https
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/Cas9, tissue engineering, scRNA-seq, proteomics, process automation etc. We offer an extremely international, well-equipped and productive work environment. Funded by an international research
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involved in the further development of a computational multi-physics simulation framework in C++ and its application to specific research problems, mainly from materials science and process engineering
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the possibility of extension) Contract:TV-L Your Tasks Develop and implement computational pipelines for processing and analyzing ONT RNA/cDNA sequencing data. Apply machine learning and signal processing
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for an interdisciplinary “bridge-builder” who strives for Scientific Excellence and Real-World Purpose. ● Background: HCI (Human-Computer Interaction), Computer Science, Ethnography, Sociology, or a related