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machine-learning-based exposure model, forming the basis for epidemiological studies linking UFP exposure to health outcomes.
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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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such as autonomous cars and robots. Job description We have multiple open PhD positions at AVI@PRS and we are looking for motivated candidates with a strong background in computer vision, machine learning
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) fluxes, and quantify contributions of soil, branch, and understory vegetation to ecosystem fluxes. Driver analyses with machine learning approaches will provide detailed insights into the underlying
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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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microscopy data: interactions with the recently created Dubochet Center for Imaging are highly encouraged. One or two of the following research topics should be covered in the application: Machine Learning
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Location: Sofia, Sofia 1784, Switzerland [map ] Subject Areas: Computer Science / All areas Quantum Computing / Quantum Computing Artificial Intelligence Natural Language Processing Machine Learning
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method (FEM) simulations using metamodeling techniques and Machine Learning (ML). By enriching datasets and leveraging advanced simulations to optimize ML models, we seek to enhance manufacturing
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responsible for ensuring the smooth operation of the IT infrastructure and services at NEXUS. Your responsibilities are: Core Responsibilities: Setup and manage virtual machines within ETH Zurich’s