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Michael Bronstein, AITHYRA Scientific Director AI and Honorary Professor of the Technical University of Vienna in collaboration with Ismail Ilkan Ceylan, expert in graph machine learning, invites
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energy densities exceeding LMFP and competitive with NMC. A postdoctoral research position is available on this 3D-CAT project in the area of computer modelling and materials design of lithium battery
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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technical knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques
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team, your expertise in AI and other cognitive computing methodologies, such as but not limited to machine learning (ML), large language models (LLMs), small language models (SLMs), natural
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working with multiphysics and multiscale models and in accelerated methods for solving partial differential equations and scientific machine learning (physics-informed machine learning) is essential. A
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, machine-learning model development, structural sensing and health monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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. Responsibilities include querying databases, data processing, supervised and unsupervised machine learning, deploying production models, and communication of scientific findings via peer-reviewed publications and
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- “Risk-aware machine learning systems for safety and quality-critical applications”. He/She will carry out research in the area of machine learning and data science, and also be required to: (a