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09.07.2025 Application deadline: 01.09.2025 The University of Tübingen invites applications for four Postdoctoral Researcher positions (m/w/d, E13 TV-L, 100%) within the ERC-funded Synergy Project MANTRAMS, Mantras in Religion, Media, and Society in Global Southern Asia, specifically focusing on...
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06.09.2023, Wissenschaftliches Personal The Livestock Systems research group at the TUM School of Life Sciences is recruiting a postdoctoral researcher (m/f/d) to work on grassland restoration
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equivalent degree in agriculture, biology or any related field. You are an early career researcher not more than one year after your PhD and you have a proven track record and extensive experience with genetic
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observations, focusing on indoor environments. Qualifications: • Applicants for a PhD must hold a Master’s degree in computer science or equivalent • Fluent written and spoken English skills • Proficient C
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. Requirements: Completed university degree in computer science or applied mathematics, remote sensing, geophysics, physics, or related areas Expertise in computer vision and/or machine learning (deep learning
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mathematics, computer science, information technology, electrical engineering, physics, mechanical engineering, or a comparable qualification Sound knowledge of mathematics and physics, especially in the fields
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, computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since
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observations, focusing on indoor environments. Qualifications: • Applicants for a PhD must hold a Master’s degree in computer science or equivalent • Fluent written and spoken English skills • Proficient C
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interdisciplinary project seeks to develop new approaches to resilient and sustainable urban development, in cooperation with Karlsruhe Institute of Technology (KIT) and RWTH Aachen. For the subproject based
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
control of such systems, taking particularly into account model uncertainties as well as limitations pertaining to acquisition of data, communication, and computation. We apply our methods mainly to human