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modeling, interpretable and explainable machine learning, or hybrid modeling by combining process-based and data-driven approaches. Besides your own main project focus, you will contribute to the supervision
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Zurich and is supervised by Prof. Livia Schubiger. The candidate will work with the IRDS group on projects that leverage NLP, causal inference, and machine learning to explore norms related to gender-based
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magnetic moments of circularly polarized / chiral phonons in quantum paraelectric materials. Job description The postdoctoral researcher will develop machine-learned force fields trained on density
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image processing techniques and modern machine learning approaches to extract meaningful quantitative information from complex biological images. The successful candidate will contribute to projects
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treatment of the xenon and argon liquid phase using electronic structure calculations. Developing computer code for computing ionization rates with general dark matter-electron interactions. Exploring
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100%, Zurich, fixed-term The ODI group at the Institute of Machine Learning is looking for highly motivated postdoctoral researchers with expertise in reinforcement learning (RL) to join our team
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society. We are actively committed to a sustainable and climate-neutral university . You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports
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to support computational design synthesis and generative engineering design across different representations. A variety of potential application areas will be investigated including consumer products, machine
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Geology or other related discipline Demonstrated expertise in machine learning and computer vision algorithms is necessary, with an emphasis on object tracking, optical flow and sensor fusion Knowledge
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change in society. We are actively committed to a sustainable and climate-neutral university . You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of