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Field
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/or spatial multiomics, advanced imaging, iPS cells, machine learning, and computational biology. The ideal candidate will have a passion for addressing fundamental questions in biology and an eagerness
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ranges from core areas of computer science and electronics over medical applications to societal aspects of AI. SECAI’s main research focus areas are: Composite AI: How can machine learning and symbolic AI
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
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PhD position in interpretable machine learning for dementia prediction. The project focuses on developing interpretable deep learning models for dementia prediction using multi-modal data, including MRI
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Europe. In the Monitoring & AI department, you will be involved in the development and implementation of AI and machine learning (ML) tools for monitoring and operation of CO2 storage sites. Key
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of methodologies, from in-depth behavioral assessments to computer vision, machine learning and neuroimaging techniques, we aim to uncover the complexites of neurodevelopmental disorders. Our
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09.04.2025 Application deadline: 29.04.2025 The Computational Law Lab at the University of Tübingen is searching for a PhD student / doctoral candidate in Machine Learning and Law (m/f/d, E 13 TV-L
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studies in a federated environment. Collaborate closely with colleagues in cryptography, machine learning, and bioinformatics to create innovative approaches that ensure data confidentiality and scalability
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challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers
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, an interest in machine learning would also be considered a plus, especially if it can be connected to embedded or hardware-oriented applications. Applicants are required to have a diploma, master or equivalent