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encourages excellence, individual recognition and responsibility. The Faculty of Biology and Medicine (FBM ) of the University of Lausanne is inviting applications for a position of: Tenure Track Assistant
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reliability-based design optimization and hierarchical Bayesian inversion. This specific PhD position focuses on the challenges within hierarchical Bayesian inference. Job description As the successful
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English. Assistant professorships have been established to promote the careers of younger scientists. ETH Zurich implements a tenure track system equivalent to that of other top international universities
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related research directions in the eDIAMOND project, namely: Distributing model training and inference over a network of resource-constrained devices. Online, context-aware adaptation of Federated Neural
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, electrical engineering and computer science to design highly efficient and sensitive imaging and inference approaches to help guide diagnosis and treatment in cardiovascular patients. Project background Our
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in teaching. Profile Doctoral degree in biology, computational biology, applied mathematics, physics or equivalent Proven track record in infectious disease modelling, quantitative biology or related
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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
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Prof. Livia Schubiger. The candidate will work with the IRDS group on projects that leverage NLP, causal inference, and machine learning to explore norms related to gender-based and other forms
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) for engineering systems. Our research covers surrogate modeling, reliability analysis, sensitivity analysis, optimization under uncertainty, and Bayesian calibration. We are known for developing the UQLab software
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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