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ecosystem models. Experience using high-performance computing systems. Proficiency in running numerical ocean models. Familiarity with operating systems such as Linux/Unix and proficiency in shell scripting
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of generally equivalent suitability, aptitude and professional performance. Data Protection Information: When you apply for a position with the Technical University of Munich (TUM), you are submitting personal
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suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. Data Protection Information: When you apply
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equal suitability, ability and professional performance. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude
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disabilities. Applicants with disabilities will be given preference if they have essentially the same qualifications, abilities, and professional performance. The position is suitable for disabled persons
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possible, ideally June 2024. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance
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, and high-performance computing. It aims to improve the performance of the matrix-free finite-element-based framework HyTeG, in particular by techniques for data reduction through surrogate operators
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of functioning of tropical and subtropical grasslands. What we expect from you • University degree (M.Sc.) and Ph.D. in Agricultural Science, Biology, Ecology, Environmental Science or a related field. • Thorough
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performance. Data Protection Information: When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take
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required to create a holistic picture. Such additional information can improve the performance, help to reveal biases, or may enable to perform causal inference. We are interested in developing statistical