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Field
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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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experimental fluid dynamics. Experience with laboratory instrumentation, data acquisition, and coding for experiment control or data analysis (e.g. LabVIEW, MATLAB, or Python) would be beneficial. Applicants
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techniques e.g. laser and optical instrumentation; computational/numerical modelling programming skills e.g. Python, C++. Eligibility Open to both UK and International applicants, including EU applicants. How
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programming (e.g., Python/C++), machine learning frameworks, or robotics software environments such as ROS. You are motivated to work in a multi-disciplinary research environment combining engineering, AI, and
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skills (preferably Python) and experience with machine learning frameworks such as PyTorch or TensorFlow. Strong analytical and problem-solving skills and interest in mathematical research. Experience with
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science, oceanography, physics, environmental science, or a related field • Strong skills in scientific programming (Python, Fortran, or similar) • Interest in Earth system modelling and climate science
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(or equivalent) in Computer Science, Engineering, Robotics, or a related field Excellent programming skills in C++ and Python Strong motivation to conduct innovative research at the intersection of machine
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, informatics, physics or a related field strong expertise in machine learning strong interest in high performance computing on CPUs and GPUs proficiency in Fortran, Python, shell scripting proficiency with Linux
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programming skills in for instance Python, Matlab or another programming language is a requirement. Experience with geodynamic and/or landscape evolution modelling is an advantage. Experience with tectonics
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analysis is highly desirable. Experience with Earth observation or remote sensing data is a strong plus. Proficiency in programming in Python and experience with PyTorch, Scikit-Learn, or related modern