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environment, with the utmost respect for academic freedom, commitment, critical thinking and personal development. For more information please contact Prof. dr. Tim Opgenhaffen, mail: tim.opgenhaffen
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focuses on the development of secure and trustworthy AI for resource-constrained embedded systems used in power electronics and energy infrastructure. The research will investigate how machine learning
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: Your professional development is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https
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systems is becoming more important in various scientific areas, e.g. in the development of new materials for data storage, light-emitting diodes, or anticancer metallodrugs. The main goal of the thesis is
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Psicologia (DEP) da Universidade de Aveiro (UA). O concurso encontra-se aberto nas condições explicitadas no edital disponível para download em https://www.ua.pt/file/89193 . Por favor, leia atentamente todo o
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application! Do you have a background in machine learning and interested in telecommunications? You have a chance to contribute to development of sensing methods for new distributed MIMO systems. Your work
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simulation. A significant part of the work will involve scientific programming, development of numerical methods, and in-depth physical analysis of flow phenomena. The ideal candidate is passionate about new
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studies in healthcare environments, such as observations and interviews, with prototype design and development. The project will develop new knowledge on how robots in clinical settings can communicate
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responsible for the evolution of this network, one needs to take into account other parameters related to the nodes: pages can for example be characterized by their size, quality & popularity; contributors by
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, please visit: https://qbm.genzentrum.lmu.de/application/ Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content