158 parallel-computing-numerical-methods "Simons Foundation" PhD positions in Denmark
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Job Description Would you like to become part of the solution toward green energy transition, by helping develop the methods for modeling future power and energy systems? The Renewable Plants in
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for research and innovation in the area of food allergenicity prediction. Responsibilities and qualifications In this PhD project you will contribute to the development of innovative methods allowing
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of the PhD study programme, please see DTU's rules for the PhD education . Assessment We will be using shortlisting based on educational background, experience and preferred qualifications and call a number of
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process. An integral part of the project will be the development of enhanced data-driven physics methods to achieve reliable prediction of material removal rate and material removal distribution
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-situ spectroscopic and microscopic methods, including XRD, Raman spectroscopy, TEM, and XPS. Evaluating catalytic performance for various electrochemical reactions, such as the oxygen reduction reaction
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qualifications we are looking for: Excellent knowledge and practical experience on current molecular microbiology methods Experience with genomic and transcriptomics data analysis is beneficial. Experience with
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and machine learning, you will help develop new methods for understanding complex failure mechanisms—an area where existing industrial knowledge remains limited. The project will be executed in three
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power electronics devices. Design methods: Develop novel design methods for power electronic converters involving advanced optimization methods Simulation: Learn advanced simulation tools such as Ansys
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in functional genomics methods (e.g., single-cell and bulk RNA-seq, ATAC-seq and ChIP-seq) and computational data analysis is considered highly advantageous. Selected references: Jakobsen et al., 2024
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process. An integral part of the project will be the development of enhanced data-driven physics methods to achieve reliable prediction of material removal rate and material removal distribution