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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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, 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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of the project team. Key Skills & Experiences This project will require previous expertise in computational mechanics (preferably finite element methods – with analysis being undertaken in open-source code MoFEM
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codes, finite element or finite different methods, peridynamics, phase field models, multi-objective optimisation methods, CAD. Demonstrated ability to adapt to fast-changing project direction and learn
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of the project team. Key Skills & Experiences This project will require previous expertise in computational mechanics (preferably finite element methods - with analysis being undertaken in open-source code MoFEM
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, architecture, and/or industrial design. You also possess: Strong analytical skills and innovative attitude Previous experience with finite element simulations and/or rapid prototyping Good programming and image
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computational mechanics of structures. Strong foundation in shell theory, elasticity, and variational mechanics Experience developing custom numerical solvers or using advanced finite element platforms (e.g
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the relevant area of expertise, including numerical simulations and laboratory experiments. Demonstrated experience with the finite element program ABAQUS. For best consideration, applicants must submit
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. The candidate should have excellent grades from the bachelor and master level courses in mathematics and mechanics as well as appropriate skills in programming and finite element analysis . Proficiency in
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working in radiological environment. Experience in heat transfer and thermal modeling/simulation using finite-element analysis (FEA) or other software. Ability to work within a multi-disciplinary team