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at the Senckenberg Research Institute and Natural History Museum Frankfurt, starting as of 01. May 2026: PhD Position (m/f/d) in Invertebrate Genomics / Bioinformatics (65%) Location: Frankfurt Employment scope: Part
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response to specific triggers, such as TGFB1-mediated epithelial-to-mesenchymal transition, a process that plays a key role in the formation of cancer metastases. Long term, this project aims to expand its
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the subcellular to the patient level. PhD projects range from the analysis of basic cellular processes to clinical translation, from the application of novel biological approaches to the development of new imaging
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Your Job: As part of your doctoral project, you will work on the production of the energy carrier dimethyl carbonate (DMC) using an innovative, sustainable, and catalytic process that exploits
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Your Job: Possible doctoral research topics: Designing processes and plants for the synthesis and use of chemical hydrogen storage Integration of chemical hydrogen storage systems into industrial
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Your Job: Conducting in-situ and in-operando Raman experiments on glass corrosion Developing and constructing fluid cells with integrated alpha radiation sources Performing post-mortem analyses (electron microscopy e.g. EPMA, SEM, and X-ray methods e.g. µCT, XRD) Preparing and evaluating...
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-supervised by a bioinformatics-focused and a biology-focused PI. A Master’s degree or equivalent in natural or computer sciences with excellent marksand a very strong experience in single-cell sequencing
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communities and interfaces to higher-level grids (electricity) for stable operation and effective market participation Supporting case studies with municipal and regional partners to bridge research and real
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staff position within a Research Infrastructure? No Offer Description Work group: Institute of Materials and Process Design Area of research: PHD Thesis Part-Time Suitability: The position is suitable
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Job related to staff position within a Research Infrastructure? No Offer Description PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1