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Connallon): Meta-analysis and modelling of why additive genetic variance for fitness is so high, and what it means for adaptation and population viability (no prior modelling experience needed). (Lab: https
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). The role combines quantitative epidemiology, mathematical modelling and field epidemiology. The post holder will undertake epidemiological and statistical analyses of field data, contribute
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the interplay between quantum mechanics and gravity in the low-energy regime, with particular emphasis on theoretical and phenomenological models in which gravity is described as a quantum, semiclassical, or
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Engineering (DTU Construct), Technical University of Denmark (DTU), you will help advance the state of the art in multiphysics modelling through a unique international research collaboration involving DTU
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patient outcomes. More information about the lab can be found here: https://www.nathlab.org As a successful candidate, you will: Develop AI/ML models to predict patient outcomes, treatment response, disease
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based on Artificial Intelligence, Machine Learning and Data Science for the modelling, analysis and interpretation of complex biomedical systems. Research activities will include the design and validation
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pavement networks. This position will focus on modeling and optimizing pavement performance under evolving climate and hazard conditions. This position will advance modeling of pavement life-cycle
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Research Infrastructure? No Offer Description Mission: Design and carry out the control of operations with turbine pumps. Functions to be developed: Develop advanced models of hydraulic pumping stations in
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disturbances. Current control methods generally rely on simplified interaction models based on constant aerodynamic coefficients, quasi-static approximations, potential flow models, or experimentally identified
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modeling of complex, multi-site datasets. In this role, you will bridge the gap between complex data infrastructure, cutting-edge machine learning, and synthetic data generation—building automated