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must have a professionally relevant background in Applied/Numerical Mathematics, Physics, Fluid Mechanics with a solid education in numerical methods for solving partial differential equations. Master
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or physics or related fields Documented practical wet lab experience and basic skills in organic chemistry Documented basic knowledge and some practical experience in programming and numerical methods. Foreign
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or more of the following topics: numerical methods for (partial) differential equations. optimization or inverse problems. data assimilation or uncertainty quantification. agentic and generative AI. solid
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. Required selection criteria You must have a professionally relevant background in Applied/Numerical Mathematics, Physics, Fluid Mechanics with a solid education in numerical methods for solving partial
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education in numerical methods for solving partial differential equations. Master students can apply, but the master's degree must be obtained and documented before starting the position and no later than
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or more of the following topics: numerical methods for (partial) differential equations. optimization or inverse problems. data assimilation or uncertainty quantification. agentic and generative AI. solid
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software. Required selection criteria You must have a professionally relevant background in Applied/Numerical Mathematics, Physics and/or Ecology with a solid education in numerical methods for solving
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The position will be attached to the project “SURE-AI” (http://www.sure-ai.no/ ) funded by The Research Council of Norway, and lead by Simula Research Laboratory. The main focus of the research will be
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flumes to study entrainment is an advantage Experience with numerical methods in general, and particle tracking in particular, is an advantage Applicants must be able to work independently and in a
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criteria It is beneficial if the candidate has a strong background in Numerical methods Elasto-plasticity Wave propagation in solids and porous media Blast, impact or shock loading Programming and scientific