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approaches; network design and analysis; and other related topics in optimization, modeling, and decision sciences. 2. Statistics: Candidates interested in this position must have solid foundations in
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risk from future pharmaceutical and medical device innovations. You will collaborate with a world-class network that includes the MHRA, NICE, the FDA, and leading industrial partners. Manchester’s
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/bayesian/deep-learning analyses, with functional validation in spruce via CRISPR-Cas9 and nanoparticle delivery. The postdoc will join Professor Nathaniel R. Street’s team at UPSC, working closely with
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restoration ecology (see https://www.slu.se/en/about-slu/organisation/departments/department-of-wildlife-fish-and-environmental-studies/ ). The department has many international employees and well-established
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possible date, preferably by 1st April 2026. This is a full position (100%) limited to 3 years. This PhD position is available within the EU-funded Marie Skłodowska Curie Doctoral Network on Low Data Machine
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-Nicholson Brain Institute (SNBI ) , the FAU Institute for Human Health and Disease Intervention (I-Health ) and the Institute for Sensing and Embedded Network Systems Engineering (I-SENSE ) is pleased
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funded PhD position on Uncertainty Quantification and Technology Qualification for Advanced Wind Turbine Components. This position is part of the MET2ADAPT Doctoral Network (Meta-Materials and Meta
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impact-based health early warning systems. The successful candidate will join the research team of Dr. Joan Ballester Claramunt (https://www.joanballester.eu/ ) at ISGlobal within the framework
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getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied
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to make decisions for localization, navigation, and cooperation. Within the ERC Starting Grant project CUE-GO – Contextual Radio Cues for Enhancing Decision-Making in Networks of Autonomous Agents