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equivalent to a two-year master's degree. Your academic background needs to be relevant to the above-stated project objectives, e.g., civil engineering, mechanical engineering, physics, or applied mathematics
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model due to the mathematical challenge of solving the multiple partial differential equations simultaneously. With the support of the combined sponsorship from the university and industrial partner
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multivariable statistical methods. Support for skills development is provided within the Horse Microbiome Research Group and the university’s Doctoral College . Delivery of this project in collaboration with
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corresponding knowledge in another way. A successful candidate should have excellent study results and a strong background in mathematics. The applicant should be skilled at implementing new models and algorithms
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experience in conducting in vivo tests. Laboratory experience in the collection and processing of biological samples and in vitro tests. Proficiency in statistical data analysis and writing scientific
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University of Basel, Condensed Matter Theory and Quantum Computing Position ID: University of Basel -Condensed Matter Theory and Quantum Computing -PHD [#21542] Position Title: Position Type: Student programs Position Location: Basel, Basel-Stadt, Switzerland [map ] Subject Area: Theoretical...
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, Cascais, Riga, Vilnius, Melsungen, Ciampino, Urla and Rhodes. The PhD project will involve: The use of data analytics (statistical models, machine learning, uncertainty quantification) to monitor and
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Degree Doctor of natural sciences (Dr rer nat) Doctoral degree or degree awarded by University of Bonn Course location Bonn In cooperation with Bonn International Graduate School of Mathematics
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MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
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the carbon footprint of milk production. The project will apply advanced statistical methods, artificial intelligence, and cutting-edge genetic models to support and enhance management and breeding decision