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(target journals: International Journal for Numerical Methods in Engineering – IJNME). Deep learning algorithms for high-temperature multiphase problems (target journals: Computer Methods in Applied
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well as in use of numerical methods via collaboration with RICAM experts the opportunity to complete a high-quality dissertation within an excellent, collaborative, and transdisciplinary research environment a
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Surgery Stanford Departments and Centers: Surgery, General Surgery Postdoc Appointment Term: 1 year Appointment Start Date: July 1, 2026 Group or Departmental Website: https://med.stanford.edu/gensurg
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at the crossroads of AI, machine learning, bioinformatics and genomics, and in developing new methods rather than just applying existing ones, we'd like to hear from you. Website for additional job details https
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Numerical relativity, machine learning Where to apply
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to sign the contract. More information is available on: https://www.dges.gov.pt/pt/pagina/reconhecimento . Workplan and the objectives to achieve: This work aims to develop a numerical approach based on
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of the hotspot quantification with the nanoagent size and the optical fluence for instance, and (3) numerically modeling the hotspot measurement with the photoacoustic method to link the mesoscopic measurement
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measurement techniques). Desirable additional qualifications include knowledge in additive manufacturing (3D printing) and experience with numerical simulation methods (e.g., finite element methods, FE
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, Process Engineering, Computational Science, or a related discipline Strong foundation in fluid mechanics, gas–liquid two-phase flows, numerical methods (FVM, FEM), and two-phase flow instrumentation
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-Documented ability to teach a range of core and advanced courses in mathematics (e.g., calculus sequence, linear algebra, differential equations, probability and statistics, numerical methods, optimization