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Field
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(structural integrity monitoring) and Dr. Francisco de Nolasco (graph neural networks). Additionally, you will be part of large and vibrant group of doctoral and postdoctoral researchers (∼20) involved in both
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qualified, those with disabilities or with equivalent status pursuant to the German Social Code IX (SGB IX) will receive priority for employment. Please submit your detailed application with the usual
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. The project focuses on developing information theory, coding schemes, and other algorithmic methods for DNA data storage. Here is a video on the topic: https://www.bbc.com/future/article/20151122-this-is-how
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learning. The project involves a collaborative team, including a postdoctoral researcher and a PhD student, with specific objectives: Define and acquire a comprehensive database of high-quality video priors
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experimental systems for cryogenic measurements Development of a microwave quantum control & readout stack Development of Python code to operate quantum systems Detailed experimental characterization
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will organize several research-related activities, such as workshops and seminars throughout the project period. The work is supposed to empirically test hypotheses rooted in economic theory. The center
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, gathering and coding morphological and geospatial data. You will be encouraged to collaborate in writing the publication arising from this work. Student profile: The applicant must be meticulous, enthusiastic
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the collaborative interaction of the student and the supervisors who will actively participate in all stages of the project. Input data and training for the use of the code and global sensitivity analysis techniques
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, computational model development, data processing, and code implementation in close cooperation with scientists. The position is limited to 3 years. Equal opportunity is an important part of our personnel policy
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academia and industry. Requirements The following qualifications are required: Solid knowledge in mathematics and statistics, in areas such as linear algebra, probability theory, machine learning, high