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will be to: Model the optical, mechanical and optoelectronic properties of the fibers using ray tracing and finite element method models; Select and characterize soft materials for the fibers, and use
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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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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
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optoelectronic platform for in vivo monitoring of brain organoids allowing for modeling of the diseases. The platform consists of two or multiple compartments which allows to monitor interactions between organoids
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interest in information processing in humans and computers, and a particular focus on the signals they exchange, and the opportunities these signals offer for modelling and engineering of cognitive systems
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, analytical chemistry, neuroethology and collective animal intelligence to develop predictive models on honeybee behaviour in response to chemical cues. If you care about biological diversity, sustainable
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plastic conversion and micropollutant degradation. Assess catalyst durability and recyclability under realistic conditions, including continuous-flow or membrane-integrated systems. Collaborate with
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, through developing predictive models and new experimental methods and instrumentation, to design creative and cost effective CO2 trapping processes. The need is urgent, the task is challenging and a
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reactive gases for anion incorporation and retention from 150 K to 1400 K temperature, and from 1E-7 mbar to atmospheric pressure. All tools are glovebox-integrated and set up for high-throughput deposition