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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicant will be made by Asst. Prof. Eli N. Weinstein. We offer DTU is a leading technical
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-analysis pipelines (statistics, mathematical modeling, and ML) for terabyte-scale 3D histology images, from preprocessing to analysis and validation. Handle and visualize large 3D microscopy datasets. Image
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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security
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Description The Unsteady Flow Diagnostics Laboratory (UNFoLD) led by Prof. Karen Mulleners at EPFL in Lausanne is looking for multiple PhD students to join the group in the fall of 2025 or early 2026
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numerical calculation skills and mathematical modelling skills Strong skills in solid state physics and quantum mechanics Experience in theoretical modelling and experimental investigation of optical devices
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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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least one of areas like animal communication research, probabilistic modeling, or language evolution is a strong requirement. As the position involves computational / mathematical modeling in the form
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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Engineering, Operations Research, Civil Engineering, Computer Science, Data Science or a related field, from a university/department with a strong international research reputation Strong mathematical and