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physics can be incorporated in various ways. Two methods now researched most intensively are i) trainable machine learning pipelines may embed differentiable physical models, and ii) the learning process
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design next-generation computer architectures for running large AI models on embedded and edge systems under strict timing, energy, and memory constraints. You’ll explore hardware-aware optimization and co
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the beginning and there is still much to be learned! You will lead a project that centers on how tactile end organs assemble, function, and recover after injury. You will be using non-standard animal models
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combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real-world energy applications, the project aims to better capture the dynamics of urban infrastructures
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efficiency, and resource utilization. Strong expertise in machine learning, deep learning, and advanced time series modeling Additional education in economics (e.g., a completed Master’s or postgraduate degree
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algorithms and routines for image processing, image reconstruction and enhancement, deep learning model training and inference, explainability/visualization, and statistical analysis of AI performance. Conduct
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contributions as a software engineer for a wide range of projects requiring computing systems design and realization, including machine learning (ML) and artificial intelligence (AI) applications including
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component disciplines; in explainable multi-modal deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The researcher will conduct internationally-leading research in
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inference, and Machine Learning methods. In addition to leading their own research projects, the appointed candidate will have the opportunity to contribute to the projects of PhD students in the group, as
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automates building and modifying surface structures, submitting DFT calculations, post-processing electronic structure and vacancy energies, and extracting machine-learning descriptors for modeling oxygen