65 post-doc-in-wireless-communication-and-networks-2016 PhD positions at Technical University of Munich
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of Munich (TUM), Campus Heilbronn. We are looking for exceptional candidates who are interested in pursuing a PhD in either theoretical computer science or graph and network visualization. We seek PhD
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on an important topic in a well-funded multi-disciplinary international training network. The training involves multiple activities, in addition to your research, and secondments across our partners. Overview
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written and spoken German and English. • High level of initiative, analytical thinking, teamwork and communication skills. How to apply: • Applications should include a CV, electronic copies of your
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10.03.2023, Wissenschaftliches Personal We are looking for a motivated Ph.D. student or post-doc interested in developing novel processes that boost the production of bio-based liquid fuels and
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, natural hazards management or related fields Interested in protective forests and their management Good quantitative skills (e.g., data analysis, simulation modelling, remote sensing) Good communication
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involved in teaching at under/postgraduate level as well as funding acquisition and (global) outreach, if desired. International networking and collaborations are regarded as an integral part of the PhD
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networking, enable internationalization and mobility, and create a collaborative environment. TUM and the CRC embody a university culture that is characterized by cosmopolitanism, mutual appreciation, thriving
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-situ measurement network and perform terrestrial laser scanning, analyzing microclimate data and their relation to forest structure, and using optical satellite time series and radiative transfer models
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03.06.2025, Wissenschaftliches Personal Chemical signaling, the most ancient and widespread form of communication, plays a crucial role in maintaining species boundaries through exclusive
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning