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medical machine learning for a talented postdoctoral researcher (f/m/d) to deepen their expertise and interest in machine learning for medical image analysis and build their early scientific career. About
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apply for stays in Europe. Travel grants are awarded for up to 3 months and encompass a contribution which may cover the expenses for travel, lodging, and course fees. Target Group PhD students or medical
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, transforming the EU into a modern, resource-efficient, and competitive economy. Responsibilities and qualifications The focus of this PhD/Postdoc project is to develop a new Li-operated potentiometric
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-to-abate sectors, but it is not yet economically viable in most cases. This postdoc position investigates the impact of different financing schemes (e.g., public, private, blended) on the feasibility
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available in the further tabs (e.g. “Application requirements”). Programme Description Applicants holding a PhD or who are eligible to be a junior professor in the historical humanities are invited to apply
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scientific career. About us TUM’s new Computational Pathology and Medical Machine Learning lab (*2021) develops methods of machine learning (ML) and artificial intelligence (AI) for the analysis of digital
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on the nanoscale (previous works e.g.: https://www.nature.com/articles/s41563-019-0555-5). You will also supervise one PhD student who will work on a complementary topic guaranteeing quick output and an ideal
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
11.02.2022, Wissenschaftliches Personal The Chair of Information-oriented Control (ITR) offers a PhD/PostDoc position within the 6G-life Research-Hub „Digital transformation and sovereignty
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22.03.2021, Wissenschaftliches Personal The 3D AI Lab at the Technical University of Munich is looking for highly motivated PhD students and PostDocs at the intersection of computer vision, machine
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- PhD student in quantitative verification interested in co-developing Automata Tutor - main developer of Automata Tutor Positions in the Formal Methods for Software Reliability group of TU Munich led by