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Field
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Science, Engineering or other Machine Learning-related field. Programming experience in MATLAB, Python, C++ or other relevant language and experience in deep neural networks. Experience and demonstratable knowledge in
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developing and implementing algorithms for processing, imaging or inversion of seismic data, preferably using MATLAB and/or Python. Experience or demonstrated ability in processing and analysis of surface
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on optimisation techniques and differential equation discretisation schemes will be developed for solving the developed mathematical models. Computer codes in Python/Matlab/R implementing these models and numerical
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science and machine learning Knowledge with Python or Matlab. Application process Please send your CV, academic transcripts and brief rationale why you want to join this research project via the HDR
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of power system operation, planning and resilience. Good programming skills (e.g. GAMS, Python, Matlab). Demonstrated high level interpersonal and communication skills with the ability to work
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developing scientific software (using any of these languages/libraries: Python, Julia, C++, C, Fortran, Matlab, Fenics/FeniX, MFem, deal.II, libMesh, PETSc, Trilinos, Pytorch, TensorFlow, Jax, Keras, Pandas
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neuropathic pain. The project will use Matlab Simulink and Systems Composer to map the following neuropathic pain models into one architecture. Peripheral Nerve Injury Models: Axotomy model (complete sciatic
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Learning, Dynamical systems theory or knowledge of some of the above and willingness to learn other fields. Must have Python, R or Matlab programming experience. Project funding Project based scholarship
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background mathematical knowledge, including differential calculus (e.g., partial derivatives) and matrix determinants. The student should also know how to program with either Matlab, Java, or Python. Ideally