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Max Planck Institute for Heart and Lung Research, Bad Nauheim | Bad Nauheim, Hessen | Germany | about 1 month ago
, the candidate should have extensive knowledge of DDA and DIA proteomic data processing using MaxQuant or similar software packages. Your responsibilities The successful candidate will focus on developing methods
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 21 days ago
information, visit our website (www.ds.mpg.de/lmp ). Your profile We are looking for excellent, enthusiastic and self-motivated researchers with relevant background and good communication skills to join our
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the development of computational methods for genetics, high-throughput omics data and causal discovery. Our interdisciplinary and international team is jointly located at DKFZ and EMBL Heidelberg, and
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 3 months ago
develop our state-of-the-art imaging systems by optimizing the hardware and integrating real-time data processing and analysis through machine learning techniques to achieve precise characterization
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Max Planck Institute for Plasma Physics (Greifswald), Greifswald | Greifswald, Mecklenburg Vorpommern | Germany | 2 months ago
explicitly encourages women to apply for this position. The IPP is committed to employing more disabled individuals and especially encourages them to apply. For information on data protection and the handling
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chronometabolic research Analysis and quantification of circadian rhythms by rhythm analysis software (Cosinor, JTC cycle, R etc.) Rhythm analysis in human 24-hour time series data and omics data Writing
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Deadline: October 31, 2025 Further information: Contact Geoffrey Andama at geoffrey.andama@sund.ku.dk or g.andama@muni.ac.ug
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us We are TUM’s unique Pathology AI lab developing new machine learning (ML) methods for automatically analyzing digital pathology data and related medical data. Such methods include the automatic
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. Severely disabled persons are given priority in the case of equal suitability. For further information, please contact Fr. Dr. Ekaterina Legchenko (ekaterina.legchenko@medma.uni-heidelberg.de ), phone +49