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. You will draw on ideas from Bayesian optimization and Bayesian deep learning, generative modelling, high throughput screening, and combinatorial synthetic chemistry. Responsibilities and qualifications
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, graphical models, and/or Bayesian methodologies for resolving disease heterogeneity, identifying gene-gene networks, or improving integrative genomic prediction models for common complex human diseases, with
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linear ballistic accumulator models, diffusion models, biased competition models, or Bayesian models. During the employment, the candidate is expected to engage in the development of computational models
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machine learning for transport simulation. A core innovation involves Bayesian metamodeling techniques to construct fast surrogate models of the simulation space, enabling efficient scenario analysis
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expression and developability. Propose and validate optimization tools for performing (Bayesian) design of experiments. System validation and iterative refinement based on empirical data. Test and refine
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possible thereafter. The aim of this project is to advance the development of multi-trait Bayesian linear regression models that enable the sharing of genomic information across traits and biological layers
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stakeholders Excellent communication skills Demonstrated technical skills in field work, GIS, multivariate statistics, Bayesian statistics and modelling. Who we are The Department of Ecoscience is engaged in