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closely related field, with a strong interest in biological systems are particularly encouraged to apply. We seek candidates with expertise in some of the following areas: molecular dynamics, Monte Carlo
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, instrumentation, signal processing, biomedical optics, wearables, light-tissue interaction, statistical analysis, design of optical systems, Monte Carlo modeling. Preferred Qualifications Education: No additional
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, geometric modelling, acoustic signal propagation, Monte Carlo simulation methods, decision theory, uncertainty quantification, machine learning. Applications and areas of key innovation Image analysis
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, sensing techniques, optimisation theory and algorithms, multi-modal data processing, high-performance computing, mathematical image analysis, geometric modelling, acoustic signal propagation, Monte Carlo
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experiments, including setup of detectors, electronics, and data acquisition systems. Experience analyzing complex experimental and Monte-Carlo simulated data to optimize the analysis of raw detector data in
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technical and scientific development of these facilities. The candidate will have the opportunity to work with data and Monte Carlo simulations from both projects. They may also contribute to the development
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analysis related to sampling, optimisation and learning problems in high dimensions. Examples of current research topics include convergence analysis of Markov processes, efficient Monte Carlo methods, large
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by time of appointment. The proposed research will leverage multiple computational many-body techniques (including classical and quantum Monte Carlo, molecular dynamics, and ab initio methods) and
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: Experience in radiological risk assessment Experience in biokinetic model development Experience with Monte Carlo radiation transport software and applications Experience with numerical computing using
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financial dynamics Apply machine learning and Monte Carlo techniques to simulate complex decision scenarios Contribute to a growing, interdisciplinary field that redefines biodiversity through the lens