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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 2 months ago
tissues and organs as spatially organized metabolic and chemical landscapes using imaging mass spectrometry. The PhD project combines spatial metabolomics, spatial exposomics, and tissue morphology
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to regulatory agencies, investors, pharma companies etc. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ What you’ll do: Develop models
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) Positions PhD Positions Application Deadline 30 Nov 2026 - 23:00 (Europe/Paris) Country Germany Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 2 months ago
, we combine imaging mass spectrometry with digital pathology and computational data analysis. The PhD project "Computational Imaging Mass Spectrometry: Spatial Metabolomics, Spatial Exposomics, and
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. The project combines quantitative modelling of markets and the wider energy system with empirical analysis of how flexibility is created, priced, and traded by market participants. A central objective is to
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modalities in the rodent brain (3D light-sheet microscopy, spatial transcriptomics and MRI of the same brain) to learn MRI contrasts that can depict neuronal and glial cell density and morphology. You will
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including sc/snRNA and spatial transcriptomics, patient-derived models, systems biology and AI platforms Opportunity to obtain a PhD within the U Strasbourg MD-PhD program Tenure track program at Inserm and U
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modalities in the rodent brain (3D light-sheet microscopy, spatial transcriptomics and MRI of the same brain) to learn MRI contrasts that can depict neuronal and glial cell density and morphology. You will
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large spatial and temporal scales. Experience in the conceptualisation and development of new methodological approaches for analysing and modelling species range dynamics, functional trait variation
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Contribute to the analysis of single-cell RNA-seq, spatial transcriptomics, and multi-omic datasets Apply computational and machine learning approaches to build mechanistic biological models and rationally