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) that encodes transient cellular events into DNA and reads them out by sequencing. Computational challenges include detection of biological signals while applying Record-seq to complex in vivo environments
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the interrogation of chiral systems down to the nanometer scale. Project background Chirality describes whether an object is non-superimposable with its mirror image. Despite being a purely geometric property
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. Utilize relevant technologies such as containers, object stores, and Kubernetes. Be versatile, display leadership qualities, and show enthusiasm for tackling problems and contributing to maintenance across
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culture. Method development: Shape parameterisation; learning objective functions for mechanism design; build end-to-end pipelines using embeddings and generative models (e.g., GANs, VAEs, Diffusion
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Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.Curious? So are we. We look forward to receiving your application including the following
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to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Curious? So are we. We look forward to receiving your application including the following documents A short
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recovery trajectories and injury patterns. Integrate personalized physiological measurements into a recovery prediction model, while adapting Bayesian Neural Networks for SCI data and analyzing the impact on
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aims to address this critical need by leveraging the power of spatial transcriptomics (ST) and high-plex immunofluorescence (IF) on a large cohort of archival CRC tissues. A key objective is to recapture
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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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the admission requirements for a PhD at ETH Zurich Experience in machine learning, optimization, or AI-driven decision-making Preferably with knowledge of Bayesian optimization or Gaussian processes