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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
. Responsibilities and qualifications Your overall focus will be to establish and lead a strong research program in the field of synthetic biology and metabolic engineering of non-model microorganisms, with the aim
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Degree Doctorate Course location Potsdam In cooperation with The innovative PhD and postdoctoral scholarship programme is offered in conjunction with the Faculty of Digital Engineering, a faculty
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with microstructural features and failure mechanisms Development of models to describe degradation mechanisms and predict component lifetime Presentation of research findings at project meetings
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the third year. The position is subject to the approval of project funding, which is still pending. Your tasks The advertised radioecology-oriented doctoral program is being carried out in a joint project
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effective for designing and optimizing applications for reconfigurable/spatial computing architectures (HW/SW co-design)- Extend or build simulation or modeling frameworks to support systematic exploration
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 6 days ago
for highly-motivated and qualified candidates to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting
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specimens. Key Duties & Responsibilities Generation of Experimental Research Data using Mouse Model and Human Samples. Analysis of High-Dimensional Computational Data. Manuscript and Grant Writing
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for modelling infection including macrophages, organoids, zebrafish, primary and clinical samples. Embedding within the Institutes of Biology and Chemistry at Leiden will enable the candidate to maximize
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Centre for Health Economics, Monash University Centre for Health Economics, Monash Business School, Integrated PhD Program 2026 Location: Caulfield campus, Monash University, Melbourne, Australia
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases