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with a considerate link to applications in the engineering or natural sciences. Possible but not exclusive areas are applications in the engineering and natural sciences modern methods of numerical fluid
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projects and newly-proposed projects, development of new statistical methods that address specific questions arising in cancer research, and eventually, scientific leadership of a biostatistics shared
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to climate neutrality of the power, industry and building sector. This involves empirical, theoretical and numerical methods. For the position, experience with questions relating to electricity market design
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theories and numerical methods, carrying out and analysing field and remote sensing observations and conducting and analysing numerical model simulations. The PhD position is funded by the German Research
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are essential. You should have expertise in at least one of the following areas: theoretical modelling, machine learning, artificial intelligence, or numerical methods for climate systems, and be confident in
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computing (HPC). This position offers an exciting opportunity to work on cutting-edge research projects at the intersection of numerical linear algebra and advanced HPC. The candidate will join an
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attention is paid to the following Knowledge and skills in numerical analysis, specifically numerical methods for differential equations and numerical linear algebra are required. Knowledge in applied
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the theory of quantum graph states. Additional expertise in computational methods would be useful but is not necessary. The Postdoctoral and Senior Research Associate positions will also involve
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statistical methods. We are committed to supporting and developing our team members, through attendance at conferences and access to training in research methods, and will support you to further develop your
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or a numerate discipline OR equivalent experience. Broad knowledge of probabilistic models, Bayesian inference and machine learning methods. Good knowledge of R, Python or both (links to project source