20 agent-based-modeling Postdoctoral positions at Durham University in United Kingdom
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optimisation techniques and AI-based models to support decision-making in microgrid design and operation. Working in collaboration with a leading global mission critical firm of engineers, this project offers
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motivated researchers to join the research team working on the Horizon Europe project involving both innovative decarbonisation technologies for the maritime sector and AI-based decision-making tools
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developing and implementing very large deep learning models. Familiarity with high performance computing environments (e.g., HPC clusters, GPUs, Cloud resources) and managing Linux based hardware systems
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. • To develop and improve theoretical models of fluid dynamics, solid mechanics, soft matter or active matter. • To carry out analytical calculations in the context of theoretical models of fluid
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; supervising student projects/practicals. · Demonstrable ability to model experiments using a range of software packages, such as Python, Matlab or Mathematica. · Experience of experimental
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investigate the “Solar wind outflow and open flux”. Candidates with a strong track record in solar magnetic field modelling, and/or familiarity with solar observational data, are particularly encouraged
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• Experience with super conducting microwave circuit design of fabrication • Experience of materials and/or device modelling software • Knowledge of Labview and/or Python software. How
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healthy life. Similarities in the structural and molecular organization of the division apparatus in a variety of model systems give the impression that the mechanisms underlying division are shared between
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and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high
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; supervising student projects/practicals. · Demonstrable ability to model experiments using a range of software packages, such as Python, Matlab or Mathematica. · Experience of experimental