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dynamics simulations and machine learning methods to study the structure and electrochemistry of disordered materials are also encouraged to apply. The project primarily aims to understand the complex
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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learning and simulation-based inference for searches for dark matter (or other “invisible” new physics signals) at the Large Hadron Collider, with the support of competent and friendly colleagues in
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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
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the foundation for learning, creativity and development. We welcome people with different backgrounds and experiences to apply for this scholarship, and especially encourage female applicants. Further information
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sensing, including Ultrasound and Hyperspectral Imaging (HSI), Artificial Intelligence (AI) and Tiny Machine Learning (TinyML). Duties As a Postdoctoral researcher you are expected to perform both
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the division of Data Science and AI , we develop data-driven methods and AI solutions that support intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and
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will collaborate with dedicated colleagues, have access to modern research infrastructure, and enjoy strong opportunities to attract external funding. You will have the space to make a real difference
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. The position shall include the opportunity for three weeks of training in higher education teaching and learning. Detailed description of the work duties, such as: Research within AI-based protein design
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spectral based sensing, including Ultrasound and Hyperspectral Imaging (HSI), Artificial Intelligence (AI) and Tiny Machine Learning (TinyML). Duties As a Postdoctoral researcher you are expected to perform