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responsibilities: To carry out and complete your own research towards a doctoral degree. Design, run, and analyse equilibrium simulations with a coupled Earth-system model of intermediate complexity to investigate
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experience growing, managing, and phenotyping plants in the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand
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preferably has strong programming skills and experience with the modeling and simulations of fluid or solid mechanics or ice sheet flow and deformation (for example by use of finite element/volume methods
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:100% of the full-time weekly hours Tasks: The PhD student will be responsible for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs
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combination with multi-fidelity response models. The multi-fidelity models may include combinations of physics-based response models, Artificial Intelligence (AI) models and probabilistic methods. Your
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Numerical simulations of Lattice QCD DoS Dr. Craig McNeile (craig.mcneile@plymouth.ac.uk , tel.: +441752586332) 2nd Supervisor Dr. Vincent Drach ( vincent.drach@plymouth.ac.uk , tel: +441752586335
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densification model forced by high resolution output from the regional climate model RACMO to simulate the evolution of the Larsen C firn layer in the recent past (1950 to present) and into the future (up to 2100
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section. The PhD-position's main objective is to qualify for work in research positions. You will report to the head of Department. Duties of the position Developing numerical models to simulate the thermo
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, especially in ultracold quantum gases or condensed matter theory Proven analytical, computational, and modelling skills Experience with numerical simulations of quantum or many-body systems A deep curiosity
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 3 months ago
detailed parameterised geometric models and running simulations for various operational scenarios, but also applying the simulation results to the design and verification of biological shielding components