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Python-based agent pipelines (e.g., LangGraph) and integrate diverse large language models (LLMs) and multimodal vision models. Additionally, you'll build and maintain data flows specifically tailored
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these subjects) is a must. Exprience with large-scale computations and data handling is required. Some bakground in nonlinear dynamical systems is also expected. The candidate must have excellent communication
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automating the detection of individual tree species in forests using deep learning. Specifically, you will: Focus on the application of deep learning techniques in Python to process spatial and aerial data
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mandate is to support academic groups and research, hospitals, industry, and the public sector at large, including cantonal and federal administrations. The center accompanies and supports their entire data
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channels: presentations at international conferences and workshops and publications in leading academic journals in economics. Project background We have fully vectorized data of a large number of musical
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. The platform blends large language and vision models with symbolic math and statistical tools and agent-based human-in-the-loop workflow management to drive: course-specific chatbots, automatic practice-problem
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with additional biophysical features Apply the framework to morphogenetic problems based on imaging data Run large-scale simulations on ETH Zurich’s high-performance computing (HPC) infrastructure
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capabilities of the existing C++ codebase Applying the framework to morphogenetic problems using real imaging data Conducting large-scale simulations on ETH's HPC infrastructure Performing model calibration
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large language models. Project background Language is a skill unique to humans among other animals. However, little is known about the neurophysiological processes that enable the construction of complex
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codebase used for training large generative neural network models. This role requires a strong background in machine learning, software development, and the ability to work collaboratively in a research