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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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Solid skills in statistical modeling & probability theory Experience in coding (Python, R, Julia, Matlab...) Motivation to work closely with experimental researchers Curiosity about biological systems
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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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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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have since helped halve global mortality, but this progress is threatened by rising insecticide resistance. We build quantitative, data-driven models to forecast the spread and impact of resistance
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for FGT 3.0: confidential HPC pipelines, scalable training infrastructure, and fine-tuned medical LLMs trained on clinical guidelines, evidence-based datasets, and real-world medical corpora. These models
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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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modification of primary human immune cells (T cells and macrophages). Conduct in vitro validations using advanced models, including patient-derived organoids and co-culture systems. Perform in vivo validations
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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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that autonomously optimizes 3D velocimetry measurements by dynamically adjusting camera positions and optical parameters. Integrating the framework within a digital twin environment for pre-training and simulation