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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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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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