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incorporating time-dependent source depletion. (4) Reducing uncertainty in groundwater risk assessments through refined numerical methods. (5) Applying the improved model to real-world groundwater contamination
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applications as PhD Student Position (f/m/d) (Ref. 25/11) in the Leibniz Junior Research Group “Probabilistic Methods for Dynamic Communication Networks“ (Head: Prof. Dr. B. Jahnel) starting as soon as possible
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energy through more efficient design of piled foundations. The PhD student will focus on grain scale mechanics experiments and numerical modelling using the Discrete Element Method (DEM) with the aim
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remains limited, with numerous fabrication challenges yet to be addressed. This collaborative project in close collaborration with partners at ETHZ and TU Delft aims to bridge the gap in current medical
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will be involved in various international initiatives and engaged with different stakeholders. The candidate is expected to primarily but not exclusively deploy qualitative IS methods, with specific
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on methods development in machine learning, uncertainty quantification and high performance computing with context of applications from the natural sciences, engineering and beyond. It is embedded in
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with knowledge and interest in structural dynamics, finite element analysis, programming and numerical methods. Applicants are expected to have achieved or be about to achieve a First-class honours MEng
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theories and numerical methods, carrying out and analysing field and remote sensing observations and conducting and analysing numerical model simulations. The PhD position is funded by the German Research
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acquisition and statistical methods is an advantage. Experience with numerical simulations (FEM). You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent
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) for general criteria for the position. Preferred selection criteria Background/experience within the following fields: Aeroacoustics Fluid mechanics Numerical methods Wind energy Personal characteristics