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Field
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strong affinity for language data; solid programming skills (e.g., Python) and experience with machine learning or NLP, ideally including transformer-based models and word embeddings; excellent English
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, with a start date in late 2026 or early 2027. The Laboratory of Toxicology in the ETH at the Department of Health Sciences and Technology is looking for a new PhD student with a focus on genomic
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machines Conduct simulations and experimental testing to validate system performance Document and disseminate research results through scientific publications and presentations The PhD candidate will work
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into the sample of interest. Recently we have been using AI and machine learning to predict the distortion present and significantly speed up this correction process. This PhD project will take the latest in AI
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levels. Apply a strong understanding of enterprise cybersecurity and technology security challenges. Utilize knowledge of computer network defense tools and processes, including leading commercial vendor
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language processing, large language models, machine learning, network analysis, social media analytics, and large-scale analysis of online discourse and communities. This PhD scholarship will be based within
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Familiarity with spatial analysis, GIS, or geospatial data workflows. Experience with machine learning, modelling, or systems analysis approaches Interest in resilience, sustainability, and environmental
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of Energy and Process Engineering We conduct research and teaching covering the entire energy chain, from resources to the end-user. We look at how energy is produced and used by humans and machines in a
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): · Hybrid Multiscale Modelling · Hybrid Physics-Machine Learning Analyses · Coupled Atmosphere-Turbine Models · Uncertainty Quantification in Hybrid Frameworks We offer the opportunity to work in a very
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programming skills in Python; initial experience with machine learning frameworks such as PyTorch or TensorFlow Initial practical experience from a master's thesis, study projects, internships, or open-source