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techniques (e.g., techniques for differentiating effectful programs such as gradient estimation of probabilistic programs, implicit function differentiation, compositional Bayesian inference techniques
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challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers
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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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are suitable. The aims of this project are to Review operating characteristics proposed for rare disease trials Develop novel Bayesian operating characteristics for different types of rare disease trials Apply
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creative – You bring substantial knowledge of statistical (e.g. Bayesian) methods, strong analytical skills, and creativity. Programming skills – You are proficient in Python and/or Matlab. Research
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biomarkers of treatment success in the broader context of respiratory allergy.Key objectives include:• Evaluating allergic sensitization patterns in soldiers prior to deployment using an extended panel
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for health policy decision-making, these methods will be developed using a Bayesian framework. This PhD project will deliver a substantial contribution to original research in the area of health data science
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
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processes related to carbon cycling in the soil-plant system Experience with Bayesian inference and machine learning is an asset Ability to work independently and cooperatively as part of an interdisciplinary
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and possibly thermal and radar images, including based on object detection and image segmentation, and collaborate effectively with other technical partners who will work with UAV-based radar systems