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Field
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optimization or discrete algorithms. Profound mathematical modeling and programming skills. Experience with the design and analysis of graph algorithms or multiobjective optimization models is a plus. Very good
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Your Job: This project involves laboratory experiments with three different crowd settings: a) a large group waiting in close proximity, b) a queue, and c) a crowd moving through a bottleneck. Using
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Max Planck Institute for Extraterrestrial Physics, Garching | Garching an der Alz, Bayern | Germany | 2 months ago
with at least a grade of 'good'. Experience in programming in C, C++, Python, or IDL (or any equivalent) is desirable, as well as experience in the analysis of imaging radio data. The full-time PhD
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• Highly motivated to carry out precision experiments and implement novel measurement methods • Strong initiative, effective working style • High level of creativity and drive to experiment intensely
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as well as funding acquisition and (global) outreach, if desired. International networking and collaborations are regarded as an integral part of the PhD research experience and are explicitly
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students of the REUNATECH network. Development and validation of FE models and shaking table experiments for base isolators under different earthquake effects. Optimisation of basic isolation by refining
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skills proficiency in English (level B2 to C1 according to the Common European Framework of Reference for Languages); knowledge of German would be an asset Experience in the following areas would be
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working style Fluent written and spoken English; German language skills are advantageous Please feel free to apply for the position even if you do not have all the required skills and knowledge. We may be
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experience in remote sensing and programming is a plus (e.g., using QGIS or R) Good communication skills Ability to work in a team Your tasks You will conduct research on the use of remote sensing data
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corpora data correlation. Requirements: A master’s degree in Computational Linguistics, Computer Science or related fields. Solid background in Machine Learning and Natural Language Processing Experience