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, to test their potential for exploiting temperature gradients for producing electricity and predict their long-term performance under real operating conditions. The project also includes modeling of heat
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performance, and preventing failures like fires or explosions. Current prediction methods mainly rely on extensive lab testing and modeling, using insights from destructive post-mortem analyses to improve
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imaging, infrared thermography and image-based performance modelling. You will join the Solar Photovoltaics Systems Team at DTU Electro, an internationally recognized research environment focusing
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qualifications are a plus: Experience in audio signal processing or speech processing. Experience in condition monitoring or predictive maintenance. Flexibility and self-motivation are desired skills at DTU. In
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years from January 2026, with possibility for extension. The position is associated to the ERC Synergy project RECLESS (Recycling versus loss in the marine nitrogen cycle: controls, feedbacks, and the
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create multi-fidelity predictive models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train
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to prevent disease and promote health by developing models and methods within the area of risk benefit assessments of foods. This includes epidemiological modeling with the aim to predict and prevent infectious
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potential for exploiting temperature gradients for producing electricity and predict their long-term performance under real operating conditions. The project also includes modeling of heat transfer and