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- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Ecole Centrale de Lyon
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- Delft University of Technology (TU Delft); yesterday published
- INSTITUTO DE ASTROFISICA DE CANARIAS (IAC) RESEARCH DIVISION
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completion) in applied mathematics, computer science, or a closely related field. Strong background in numerical linear algebra, algorithm design, and parallel computing. Proficiency in programming languages
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advanced many-body methods, high-performance computing, and machine learning approaches. The successful candidate will play a leading role in developing computational methods and high-performance algorithms
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Computational Fluid Dynamics. Operational skills : Physical analysis of fluid dynamics, advanced skills in programming and numerical methods, writing scientific reports and articles, presenting at scientific
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of numerical quantum many-body methods to study model Hamiltonians. Strong background in linear algebra. Preferred Qualifications: Experience with density matrix renormalization group and tensor network
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of interpretability methods to ensure ML outputs are meaningful in scientific contexts. Preferred: Background in biomedical data, healthcare, or AI for life sciences. Experience with parallel computing. Familiarity
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(multiscale, QSP, PBPK, PK-PD).Apply numerical methods, optimization, and parameter estimation to calibrate models to experimental/clinical data.Perform sensitivity and uncertainty analyses to assess robustness
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students to advance project goals. Provide technical guidance and mentoring on CFD, numerical methods, and high-performance computing workflows. 15% - Publication & Dissemination Prepare and submit
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, graduate, and undergraduate students to advance project goals. Provide technical guidance and mentoring on CFD, numerical methods, and high-performance computing workflows. 15% - Publication & Dissemination
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supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order
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image processing and analysis method development. The position builds on the lab's track-record in the field of computational imaging techniques for super-resolution microscopy and image analysis