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Field
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October 1, 2025. Job description: Contribute to research in subproject "C04 – In silico design of mol2Dmat heterostructures", especially in the field of halogen intercalation in graphitic materials and the
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application of machine learning to biomedical data ï‚· Background in computational modeling for neurobiology, including finite element modeling (FEM) or system identification methods in medical applications
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(e.g., finite element or wave propagation simulations) for defect detection and materials analysis Integrate AI, machine learning, and robotics into NDE and manufacturing processes for automation and
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three years of the abovementioned practical experiences. For all posts, preference will be given to those with knowledge of finite-element simulation, as well as product design optimisation and
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 2 months ago
validation; proficiency in Python and scientific computing, including experience with finite element methods, preferably using FEniCS or DOLFINx; strong analytical and communication skills, with the ability
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microscopy, optical interferometry, vacuum technology, finite element method simulations will be involved. Applicants should hold a PhD in Physics, Nano-science, Engineering or similar, experience with optics
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, Dental Materials, Dental Technology or a related discipline, with research experience in Non-linear Finite Element Analysis, CAD for dental prostheses, AI algorithm development using python / PyTorch, and
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microscopy, optical interferometry, vacuum technology, finite element method simulations will be involved. Applicants should hold a PhD in Physics, Nano-science, Engineering or similar, experience with optics
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finite element analysis, finite difference schemes, or Monte Carlo simulations. Mentoring Assist in mentoring graduate and undergraduate students in related projects. Collaborate with faculty and students
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: Experience in physical system modelling including finite element modelling Experience working with large codebases in open source software environments Proficient user of HPC environments including MPI