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). These collaborations enable practically relevant and breakthrough results. This team goal requires a quantitative model describing and predicting sperm motility under various conditions. You will develop the digital
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data processing, image/signal analysis, and machine learning. ✅ Familiarity with instrument control, calibration, and automation workflows. ✅ Excellent written and oral communication skills in English
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these emergent processes and is looking for a PhD student / PostDoc (f/m/d) The Mission Understanding how multicellular systems organize themselves into tissues is a central challenge in modern biology and
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into electrical signals. We identify and characterize the molecular components involved in this transduction process using state-of-the-art molecular biology, electrophysiology, and biophysical techniques. We
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Limitation:Temporary (2 years) 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 approaches
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practically relevant and breakthrough results. This team goal requires a quantitative model describing and predicting sperm motility under various conditions. You will develop the digital twin of sperm motility
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GESIS - Leibniz Institut für Sozialwissenschaften | Mannheim, Baden W rttemberg | Germany | 6 days ago
, involving software developers, language experts and language service providers. Your tasks will be: Managing the project from a content point of view, in close collaboration with a GESIS internal software
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conferences In-depth experience and knowledge in digital image processing and analysis Solid experience in other material characterization techniques Experience in the design and implementation of experimental
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internship board Career Paths Business Contacts Offers for Alumni Contact persons Research Back Research infrastructure Back Digital Humanities Center LISA+ Quantitative Biology Center (QBiC) Tübingen
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/ . Interested candidates in all related fields are invited to apply and should indicate their previous experience and topical preference in their application material. Applicants for the ERC advanced grant