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, mathematics, or related scientific disciplines. Skills in numerical tools and programming are desirable (MATLAB, python, C++ etc). Any experience or capabilities in engineering design or manufacturing methods
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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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, python, C++ etc). Any experience or capabilities in engineering design or manufacturing methods would be advantageous. Eligibility and Application Due to funding restrictions, the position is only
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awarded within 3 years in business administration, computer science, information systems, data science, or a related discipline. Programming & Data Skills: Strong proficiency in Python (e.g., NumPy, Pandas
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mechanical assembly. Competence in C/C‑like microcontroller programming and Python. Strong practical understanding of electronics, circuitry and diagnostic tools. Experience with 3D printing, laser cutting and
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or reinforcement learning, and good programming skills in Matlab and/or Python. You will have completed an undergraduate degree or MSc in a quantitative discipline. The Humphries’ group (https://www.humphries
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process simulation, techno-economic analysis (TEA), and life cycle assessment (LCA) methodologies Strong computational skills, including proven expertise in programming environments (e.g., Python, Matlab
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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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, 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