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literacy with at least basic programming skills (R, Python). Analytical mindset, with a keen interest in advancing proteomic methodologies Knowledge of cancer biology is an advantage We offer Cutting-edge
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or equivalent and a PhD (or close to completion) in computer science, math or comparable, or an applied/life science (e. g. engineering, biology, medicine) with a focus on data analysis and/or machine learning
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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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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | 2 months ago
electrophysiology, functional imaging, or light/electron microscopy Familiarity with genetic and molecular biology tools Background in computational modeling of neural systems A demonstrated ability to secure
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physics, engineering, medicine, biology or a related field Practical experience in optics, signal processing and working with experimental setups (e.g. MATLAB) Interest in medical diagnostics and innovation
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Bioprogrammable Materials is looking for an enthusiastic Post-doctoral Researcher with experience in Protein Engineering. We combine synthetic biology and biomaterials to develop smart platforms for therapeutics
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Contact persons Research Back Research infrastructure Back Digital Humanities Center LISA+ Quantitative Biology Center (QBiC) Tübingen Structural Microscopy (TSM) Research Data Management (RDM) Core
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and skills: You hold a PhD in Bioinformatics, Computational Biology, Genomics or a related field. You bring proven expertise in deep learning and statistical modelling of biological data. You have
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to 5 and more years. Requirements: • You have a PhD degree (or postgraduate degree MSc) in a computational discipline, preferably with significant experience in Bioinformatics or Computational Biology
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for livestock systems in East Africa, and in the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We