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Field
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and grippers offer improved safety and adaptability but introduce new challenges in design and control. Their development is still largely bio-inspired and trial-and-error based. Integrating flight and
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to create secure, autonomous and developable solutions that interact with each other and their surroundings, from the edge to the cloud. Project description For this position, you will be working as part of a
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assessment, you will develop new, sample-efficient optimal control approaches for gate calibration and test them in numerical simulations. You will pursue your research with the German research collaboration
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at the single-cell level, using tools from optimal transport, mathematical optimization, and machine learning. In addition to method development, the work includes applying and benchmarking algorithms on both
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hierarchies during cardiac, endothelial and hematopoietic development. Responsibility: * Develop or integrate novel statistical methods and algorithms for analyzing large-scale -omics data, including gene
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our software development team, developing novel scientific algorithms and applications in the areas of spectroscopic analysis and mining of the science data catalogues extracted from the pipelines
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Your Job: develop numerical and analytical techniques to simulate and control the time dynamics of quantum technology devices implement and optimize gate operations and artificial Hamiltonians
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. The acronym CAUSE stands for Concepts and Algorithms for - and Usage of - Self-Explaining Digitally Controlled Systems. Digitally controlled systems are ubiquitous in our everyday lives, from transportation
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supply and a path to a net-zero-emissions society. SecurEL aims to develop new knowledge addressing research challenges arising from accelerated electrification and increased use of the existing grid
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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have