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Field
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. We benefit from the different expertise, perspectives and personalities of our staff and welcome every application from qualified candidates, irrespective of age, gender, ethnic or cultural origin
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to consider the Ericksen—Leslie model with stochastic fluctuations and investigate it in terms of existence of solutions and their approximation, the associated large deviation principle and the simulation
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implementation Reference code: 50144551_2 Commencement date: 01.09.2025 Work location: Hamburg Application deadline: 13.07.2025 The Climate Service Center Germany (GERICS), a scientific organizational entity of
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within this project include: Extending DeepRVAT towards non-coding genetic variation Applying DeepRVAT to population-scale single-cell readouts Integrating population data with experimental perturbation
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) assess future changes in these patterns under different global warming scenarios. Requirements: The successful applicant should hold a MSc or PhD degree in physics, mathematics/statistics, climate science
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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the proposed research fields. The group consists of approximately 17 members at different levels of seniority. Salary is paid according to German TV-L (salary agreement for public service employees). As an equal
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) assess future changes in these patterns under different global warming scenarios. Requirements: The successful applicant should hold a MSc or PhD degree in physics, mathematics/statistics, climate science
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Senckenberg Museum of Natural History is located in a historic town with a region that is particularly close to nature and well worth living in. This position aims to describe differences in structure and
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information for ocean health, sustainable blue economy, and coastal climate risks, downstreaming the data flow from climate ensembles to coastal areas at different spatial resolutions and for selected areas, in