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(RTP) by metal-free compounds and double thermally activated delayed fluorescence (TADF) from single molecules. Work assignments The proposed postdoc project among others will include computational
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particular, this holds for the principles of electroluminescence of OLEDs based on luminescence by radicals, room temperature phosphorescence (RTP) by metal-free compounds and double thermally activated
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at the intersection of AI and advanced electron microscopy. The project focuses on developing novel self-supervised and physics-informed deep learning methods to restore and denoise Transmission
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consist solely of research collaboration with a mutual exchange of methodological and technical expertise but must also contain a well-defined training element and a qualification plan must be established
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application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Your tasks will include conducting independent research in the subject area at
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characteristics. Innovate methods for integrating photosynthetic components into material systems and devices with additive manufacturing. Functionalize biological components with technological and stimuli
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tailored materials design with advanced characterization methods to enable new device functionalities. The research aims to expand the capabilities of organic electronic devices by integrating light
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. The focus will be on developing and automatically learning new methods for efficiently solving planning tasks. The projects will involve both theoretical and experimental work. Qualifications To be qualified
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: https://wasp-sweden.org/ Project description Trustworthy machine learning is an umbrella term that provides methods and tools to ensure that AI and ML systems are verifiable, robust, secure, privacy
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: Develop biohybrid living materials and devices based on photosynthetic organisms with responsive and evolving characteristics. Innovate methods for integrating photosynthetic components into material