39 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral positions at EPFL
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the development of novel and innovative numerical techniques aiming at improving the integration between numerical simulations and geometric modelling and processing. Proof assistants such as Lean, together
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, demonstrating that AI can help make verified systems competitive with unverified systems in terms of development effort, features, and performance. Main duties and responsibilities Conducting research related
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, electrodermal activity, respiration and autonomic stress indices. Developing reproducible pipelines for data preprocessing, feature extraction, statistical modeling, visualization and documentation. Implementing
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neuroscience. Within this framework, AI models are co-developed with domain experts to unlock concrete biological questions and accelerate their translation to clinic. The large and interdisciplinary research
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(acoustic crystals). The candidate should have solid experience in the development of hydrogel acoustic metamaterials. We also welcome and can host candidates to apply for MSCA Postdoctoral Fellowships 2026
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tumor evolution requires integrating both genetic and non-genetic mechanisms. Thus, our research begins with the functional characterization of cancer-associated genomic alterations to determine how they
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communities as a model system. Main duties and responsibilities Anaerobic digestion communities are among the best-characterized and most ecologically important microbial ecosystems. Composed of diverse
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through proprioception. We develop widely-used open-source tools (e.g., DeepLabCut), train biomechanically realistic embodied agents (e.g., MuscleMimic, Kinesis, Arnold), and build AI-based models
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, to wearable sensors and actuators, as well as soft in vitro interfaces. The Postdoc will contribute to the development and verification of an optoelectronic therapy for bladder dysfunction. More specifically
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together physicists, earth and planetary scientists, chemists and biologists to understand the conditions and the mechanisms that enable life to emerge. Developing reliable methods to detect reliable traces