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Max Planck Institute for Biological Intelligence (Martinsried site), Martinsried | Germany | 10 days ago
. Demonstrated interest in animal research, particularly rodent models (experience with mouse handling or physiology is an advantage). Experience with MRI data processing, image reconstruction, pipeline
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: PhD in CS/ML/medical informatics, strong publication record, and hands-on experience with generative models in medical imaging. Postdoctoral Research Associate (f/m/d) EU Research Project TWIN-X Full
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | about 2 hours ago
organoid culture methods. Experience in computational analyses of proteomics or single-cell sequencing datasets. Experience in microscopy and image analysis. Effective collaboration in interdisciplinary
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. Responsibilities include: Designing and executing behavioral learning paradigms with social and non-social reinforcement In vivo calcium imaging during learning and sleep Quantitative analysis of neural activity
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), proteomics (LC-MS/MS), (epi)genomic data processing, multi-omics integration, machine learning approaches for high-dimensional data, confocal / two-photon imaging, tissue clearing and light-sheet microscopy
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systemic infectious processes, immune responses, and evaluating therapies, refinement measures to reduce stress and improve welfare in experimental animals are underexplored. In this 3RTG, we will address
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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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, ATAC-seq, CUT&RUN, MERFISH, Visium), epigenomic data processing (chromatin accessibility, histone marks, enhancer mapping), multi-omics integration using Seurat, Signac, Harmony, ArchR or Scanpy, machine
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efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes the evaluation
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while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes the evaluation of existing