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electron microscopy, atomic force microscopy, metal evaporation, wire bonding), performing computer-based simulations and modelling in COMSOL, physics of strongly correlated many-body systems. We offer you
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of novel physics-guided AI algorithms for drug design, integrating physics-based modeling with state-of-the-art deep learning methods. The project will focus on creating a next-generation docking framework
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, systems, and hardware design. Experience in one or more of: LLMs, AI agents, embedded ML, physical modelling and simulation Strong programming skills in Python and C/C++, familiarity with ML deployment
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near-instantaneous proliferation of comb lines and new regimes of spectral control. Project background This project will combine advanced numerical modeling with laboratory demonstrations to explore
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of information transmission, derive the theoretical models governing them and demonstrate their intriguing properties experimentally. The practical realizations of these topological metamaterials will be based
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with ex situ experiments, demographic modelling or handling large datasets as well as holding a valid driver's license is a plus. Application / Contact Please upload your application via our online
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lack of rapid tools to understand and monitor the spread of pathogens. Building on our previous work on DNA tracing technologies, we aim to develop tools and procedures to model and monitor the spread
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. Empa is a research institution of the ETH Domain. Empa's Laboratory of Biomimetic Membranes and Textiles is a pioneer in physics-based modeling at multiple scales. We bridge the virtual to the real world
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different methods such as modeling mass flows analysis (MFA), Life cycle analysis (LCA) and semi-quantitative methods for decision support for sustainable innovation. PhD Student in Safe and Sustainable Green
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reinforcement learning for large language models (LLMs). Research directions include developing next-generation post-training algorithms, exploring diffusion-based approaches to reasoning with language models