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, particularly MRI, medical physics or computational data analysis (Python/R/MATLAB, machine learning, or bioinformatics) is highly desirable. Interested candidates should send a CV to michael.chappell
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foundation in either machine learning or mathematical/computational neuroscience, demonstrable programming experience (Python/PyTorch), and the curiosity to work across disciplinary boundaries. A background in
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physics or computational data analysis (Python/R/MATLAB, machine learning, or bioinformatics) is highly desirable. Interested candidates should send a CV to michael.chappell@nottingham.ac.uk . Applications
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programming and data analysis (e.g. Python, Julia, MATLAB, C/C++, or similar) • Ability to work independently and as part of a collaborative research team Desirable skills / experience
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. Skills in numerical tools and programming are desirable (MATLAB, python, C++ etc). Any experiences with engineering design, structural/aerodynamic/aeroelasticity modelling, manufacturing/assembly process
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programming are desirable (MATLAB, python, C++ etc). Any experience or capabilities in engineering design or manufacturing methods would be advantageous. Eligibility and Application Due to funding restrictions
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CFD, thermofluids and machine learning. Experience in Python (or another language), machine learning frameworks, or CFD tools such as OpenFOAM is beneficial but not required. Applicants should hold (or
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. Programming experience (e.g. Python, MATLAB, C/C++). Desirable (but not required): Background in control theory, dynamical systems, optimisation, or machine learning. Experience with robotics, ROS, simulation
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relevant discipline in engineering, science, or mathematics. Experience with modelling, simulation, optimisation, or programming (e.g. Python, MATLAB, C++, or similar) would be advantageous, though not
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-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is desirable but learning can be completed during the PhD. Excellent