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Tübingen offers a combination of high-performance medicine and strong research. The goal of the Carl-Zeiss-Project “Certification and Foundations of Safe Machine Learning Systems in Healthcare” is to enable
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-flight measurements and defect spectroscopy Planning and realisation of 1D–3D device simulations with OghmaNano and machine learning to analyse charge carrier dynamics and loss mechanisms of organic solar
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of these patients. The goal of this project is to combine cutting-edge multi-omics technology, data analytics, machine learning and clinical samples from the human eye to decipher new insights into disease mechanisms
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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. Furthermore, we develop advanced scattering methods and machine learning tools for data analysis. For more information, see www.soft-matter.uni-tuebingen.de Qualification and skills Candidates should have good
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of machine learning and health sciences, with unique access to experimental and clinical data. Embedded in Munich’s thriving AI landscape, fellows benefit from world-class facilities, interdisciplinary
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culturing, integrating multiple automated subsystems with image-based machine learning models. Our objective is to enable robotic decision-making through machine learning, paving the way for a standardized
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omics, environmental, and chemical data, using machine learning and explainable AI. Depending on your background, interests, and evolving project needs, your work may focus on one of these areas or bridge
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Your Job: You will develop impactful machine learning techniques to deal with complex quantum states. Possible research directions and tasks include: Method development to advance neural quantum
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its detailed analysis through Oxford Nanopore Technologies (ONT). Your role will be central in creating and applying bioinformatics and machine learning tools to analyze long-read data and decipher cap