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(subproject A1): This project aims to enhance smartphone-based survey methods as one component of future multi-method travel surveys, to achieve representative samples and travel estimates, to collect
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hydrological modelling methods that explicitly use interpolation to pre-process precipitation data. In addition, the research should explore the integration of opportunistic sensor data to improve forecast
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or replace established methods from computational engineering and computer simulation (such as the finite element method) to represent and exploit relationships along the composition-process-structure-property
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include: Implementing the classical components of the Sample-Based Quantum Diagonalization [1] method within the MiMiC multiscale simulation framework Developing and integrating a communication interface
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consistent scientific methods for mobility planning and management, (2) integrate a new set of modular metrics for responsible mobility, (3) embed the planning methods into the open data AgiMo Digital Twin, (4
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computer philology also belong to the program ALT. Thus, the program is characterized by a plurality of research methods and a wide understanding of the concept of ‘a text’. Applicants are expected to have
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consistent scientific methods for mobility planning and management, (2) integrate a new set of modular metrics for responsible mobility, (3) embed the planning methods into the open data AgiMo Digital Twin, (4
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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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science. A wide range of quantum theoretical methods shall be employed. A solid background in quantum mechanics and programming skills are prerequisite for this position, as is the readiness to learn and to