79 programming-"https:"-"FEMTO-ST"-"UCL"-"https:"-"https:"-"https:" positions at ETH Zurich
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combine molecular engineering, cell programming, and chemical–biological interfacing to engineer human cells using synthetic gene circuits and biosensing platforms, develop novel biosensing systems for real
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Required Experience: PhD in Geodesy, Geomatics, Aerospace Engineering, Signal Processing, or a related field Proven experience in GNSS data analysis and processing Very good programming skills (e.g., Python
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transdisciplinary knowledge. Job description We offer a full doctoral student position in our research group. The doctorate will be conducted within the Einstein School’s doctoral program and is expected to be
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study is of highest priority. The mission concept study will finalize the required satellite architecture, conduct key technical trades, and finalize the overall mission development plan and
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novel research programme at the frontier of multimodal AI and ICU clinical cognition. Under the guidance of Prof. Jutzeler, a dedicated postdoctoral researcher, and collaborators, you will have access
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Each doctoral student will lead a coherent subproject within this broader research program: Position 1: AI for Computational Thinking Focuses on designing and studying AI-assisted programming
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programming skills in Python Experience with machine learning systems or LLM-based architectures Experience working with complex data systems or developing applied AI prototypes Familiarity with modern AI tools
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Forest Studio is designed as a modular modelling environment that integrates ecological theory, empirical data, and modern scientific programming workflows. This position focuses on advancing
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-learning models on distributed systems Strong programming skills in Python and familiarity with a modern ML stack (e.g., PyTorch, hydra, zarr, dask) and best practices MLOps Experience in handling and
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. Strong programming skills in Python and familiarity with a modern ML stack (e.g., PyTorch, hydra, zarr, dask) Experience in handling and processing large datasets or experience in high-performance