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with researchers at Chalmers and the University of Gothenburg. You will explore how Bayesian methods can enable risk-aware, real-time trajectory planning and contribute to the development of autonomous
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Department of Forest Biomaterials and Technology We are seeking a motivated postdoctoral researcher to develop and apply environmental DNA (eDNA) as a tool for early detection of forest pathogens
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modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position
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of Applied Mathematics and Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale
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of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods
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of Applied Mathematics and Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale
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medical applications. Federated Bayesian learning offers a solution to those problems by allowing multiple participants to train machine learning models collaboratively, without sharing any data. Bayesian
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Mathematics and Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational
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understanding of statistics (e.g., hypothesis testing, Bayesian statistics) Good collaborative abilities, independence, and critical thinking. Preferred qualifications In-depth experience with LLM agents
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Bayesian framework and two specific proposed lines of research: (1) constructing suitable priors via neural networks approximations, and (2) enhancing the sensitivity and efficiency of posterior diagnostics