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Fluid Dynamics (CFD) is increasingly used to predict the performance and forces acting on wind-assisted vessels, but experimental validation remains essential, particularly in complex hydrodynamic
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, computational modelling and experimental work. You’ll join a pioneering multidisciplinary team that values equity, diversity, and inclusion, gaining unique expertise in turbomachinery pump development, hydrogen
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Research theme: water wave mechanics, physical oceanography, computational fluid dynamics How to apply:uom.link/pgr-apply-2425 Number of positions: 1 This 3.5 year PhD is directly funded through
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, computational fluid mechanics, high-performance computing, and physics-informed machine learning. Affinity with physics-informed machine learning, computational VVUQ (verification, validation, and uncertainty
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of the Jalaal group at University of Amsterdam. Qualifications You have (or soon will have) a MSc physics or applied physics. Knowledge about fluid mechanics and/or experimental laser physics is advantageous
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Fluid Dynamics (CFD) is increasingly used to predict the performance and forces acting on wind-assisted vessels, but experimental validation remains essential, particularly in complex hydrodynamic
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on the development of new methods to accurately predict cavitation in heavy liquid metals through a combination of computational and experimental approaches. The computational aspect involves developing advanced CFD
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education facilities. Through this project, the student will gain highly sought-after expertise in experimental fluid mechanics which is a key identified area of growth to enable development of next
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, fluid mechanics, turbomachinery) Interest in communication and dissemination of research results, including participation in project related activities and fulfilling the obligations. Excellent written
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Degree in Maritime, Mechanical or Aerospace Engineering, Applied Physics or related field; A strong interest in both numerical and experimental fluid dynamics; Excellent analytical and problem-solving