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GC-009 in the subject line. Your application should include: Cover letter Curriculum vitae Academic transcripts Contact information for two references About LMU Munich LMU researchers work at the
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Max Planck Institute for Plant Breeding Research, Köln | Koln, Nordrhein Westfalen | Germany | 2 months ago
, maintenance and troubleshooting on an Aria Fusion cell sorter Sample preparation, cell sorting and data analysis Generation of single cell libraries with 10X Genomics, Singleron and BD Rhap-sody platforms
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for the contactless detection of plant conditions. The position is advertised as part of the international joint project ‘MULTIFUSE: Advanced Multimodal Sensing and Data Fusion for Early Digital Detection of Plant
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of great ape communication to identify evolutionary trends and simulate dynamics that might explain the evolution of common ground in humans. For more information see the following representative articles
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application from female candidates. We regret that only shortlisted candidates will be contacted. In accordance with Germany’s data protection regulations, application documents from candidates who are not
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for imaging plant tissues (rose cuttings) Realisation of a corresponding measuring stand and implementation of test series for imaging Realisation of a data processing routine for the automated detection
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Knowledge and experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl
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and statistical data analysis Excellent written and spoken English skills Experience with TMS and proficiency in relevant software (e.g., MATLAB, R, Python, or SPSS) is an advantage Key responsibilities
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corpora data correlation. Requirements: A master’s degree in Computational Linguistics, Computer Science or related fields. Solid background in Machine Learning and Natural Language Processing Experience
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morphology (future and conditional) in Spanish, Italian and French. On the empirical side, the project will deliver a theoretically informed cross-linguistic description based on data collected via