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cells Key methods will include: Gaussian Processes (heteroscedastic & multivariate) Operator-valued and deep kernels Active Bayesian experimental design Physics-informed neural networks Closed-loop
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-armed Bandits, Bayesian Optimization. Automated Model Design and Tuning: Neural Architecture Search, Hyperparameter Optimization. Computer Networking: Resource-Constrained Networking (e.g., Internet
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) distributional generalization, transfer learning, causality Multi-objective settings and alignment, RL theory Statistical learning theory, optimization (e.g., implicit bias) Robustness (broadly defined), privacy
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screens with robust guide demultiplexing and assignment, and cell-type annotation using bespoke references. Strong grounding in statistics (GLMs, hierarchical/Bayesian modeling, multiple testing) and
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/Seurat, count models, batch correction, differential analyses). Strong grounding in statistics (GLMs, hierarchical/Bayesian modeling, multiple testing) and experimental-design principles. Bioinformatics
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between Gramazio Kohler Research (Chair for Architecture and Digital Fabrication) at ETH Zurich and the Chair for Timber Structures (Prof. Dr. Andrea Frangi). Job description The objective of this PhD
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for Architecture and Digital Fabrication) at ETH Zurich and the Chair for Timber Structures (Prof. Dr. Andrea Frangi). Job description The objective of this PhD position is to investigate methods and techniques
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rocket launches has never been performed. Research Objectives: Perform and analyse lab experiments focused on alumina chemistry and microphysics Simulate impacts of space launchers on atmospheric
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. Research proposal with clear statement of objectives, expected outcomes, and schedule, including how your project would link to ongoing research and facilities at ITA or LUS (max. 2500 words excl. references
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include: Motivation letter outlining your interest in the position and relevant qualifications. Research proposal with clear statement of objectives, expected outcomes, and schedule, including how your