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Field
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and interpretable quality assessment algorithms. This research combines various machine learning topics, including uncertainty, explainability, and fairness in supervised and unsupervised deep learning
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Machine learning Experience is ideally shown through a thesis, seminar papers, or scientific publications. Alternatively, excellent grades in a respective Master’s programme. Strong intrinsic motivation
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, engineering, natural sciences or other data science/machine learning/AI related disciplines Language requirements English C1 or equivalent Application deadline January, please see website for exact date Submit
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of computational approaches to large scale simulations Basic knowledge of (geo)chemical processes and machine learning will be of advantage Expertise in Machine Learning approaches, ideally beyond neural networks
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research areas. New insights and synergetic effects resulting from collaboration between inherently different viewpoints of separate fields typically accompany this endeavour. Our task force on machine
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for data-efficient exploration and optimization within the process parameter space as well as for adaptive, data-driven machine learning to map the electrolysis process to a digital twin. Data workflows and
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data structures, machine learning, computer graphics and vision, database systems, artificial intelligence, logical methods, programming languages, computer architecture, and security, to name but a few
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development of artificial intelligence (AI) software for topology-informed biomedical image analysis and large foundation models. You will be responsible for Develop new machine learning algorithms
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-based products, is among the areas that more quickly is adopting AI. Machine learning (ML) algorithms are being developed and integrated in microscopes for its autonomous operation and in software
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for improved understanding of structural and kinetic processes in electrolytes; and machine learning concepts for improved analysis of experimental and simulated data. Material Synthesis Within this research