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Full-time onshore enrolment Strong background in fluid-structure interaction or in systems and control Solid background in mathematics (theories in both ordinary and partial differential equations
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partial differential equations; Strong interest in working in a cross-disciplinary, collaborative project at the interface of electrochemistry and mathematical modelling; Knowledge of electrochemical
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modelling and numerical methods for ordinary and partial differential equations; Strong interest in working in a cross-disciplinary, collaborative project at the interface of electrochemistry and mathematical
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mechanics, and analytical and numerical methods to solve partial differential equations. Excellent oral and written communication skills. Prior experience in computational fluid dynamics or active matter will
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, differential equations, geometry/topology, numerical analysis, optimization, and statistics. Part of the research is also carried out in close cooperation with other fields of science and technology at NTNU, as
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structure, variational structure, and symmetries, data-driven techniques to solve partial differential equations (pde) have emerged. Quantifying model uncertainty of data-based predictions is crucial
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operation, is not considered in the CMF model due to the challenge to solve the multiple partial differential equations simultaneously. With the support of the combined sponsorship from the university and
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for implementing ONNs. Modeling, simulate and benchmark different computing tasks such as combinatorial optimisation tasks and solving partial/ordinary differential equations with ONNs. Design and tapeout ONN chips
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], molecular properties analysis, analysis of adaptation and selection), proteomics analysis (including differential expression analysis, enrichment analysis, structural equation modelling, and supervised
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Requirements: Ph.D. in mathematics, applied mathematics, physics, computer science, engineering, or a related quantitative field. Strong knowledge of differential equations and applied mathematical modeling