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networks by analyzing their dynamical systems and probabilistic asymptotic behavior, improving and generalizing diffusion-based generative AI using insights from numerical and stochastic analysis, and making
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. Background: Detecting deception is an important but challenging task for numerous organizations worldwide including in the UK (e.g., Probation Service, Police). Whilst there are different approaches, the most
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asymptotic analysis and other perturbation methods, and numerical, i.e. an existing in-house code will be modified to achieve the objectives. This project offers the unique opportunity to develop strong skills
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will have a strong background in socio-technical threats and attacks, deception and social engineering, and security and cybersecurity metrics analysis (qualitative and quantitative). With a high
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magnetic components of the dynamo are to be simulated numerically. Your profile: Potential candidates (m/w/div) should hold a Masters or Diploma degree in Materials Science, Mechanical Engineering
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-speed cameras (in a newly renovated lab dedicated to our research group). A significant component of the analysis will include image processing, including data-driven methods and machine learning. You
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(Co-I) and a post-doctoral researcher focussed on numerical aspects of the network model analysis. Being part of the wider Mathematical Neuroscience research theme within the School of Mathematical
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techniques such as GMAW and laser-arc hybrid. The study shall be supported by numerical modelling and thermodynamic calculations. In the next step, the welds shall be characterized using advanced microscopy
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: Mathematics, Mathematical Statistics and Computational Mathematics. The research at the Division of Computational Mathematics covers many different areas in numerical analysis, symbolic computations
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Apply Job Type Full-time Description Job ID AF9515 -0617-1850 Position Classification FT Administrator Position Summary This position is designed to provide PhD-level expertise in helping numerous