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Field
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(Python, MATLAB) for behavioral data analysis Preferred Qualifications: Experience with rodent behavior assays Familiarity with tools like DeepLabCut, MoSeq, or Kinect-based systems Interest
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behavioral neuroscience, development, or ASD Programming experience (Python, MATLAB) for behavioral data analysis Preferred Qualifications: Experience with rodent behavior assays Familiarity
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, particularly GBS, continuous-variable QC Experience with numerical simulation, statistical estimation, or probabilistic modeling. Programming proficiency (Python, Matlab or C++), especially for numerical
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proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C++). Prior proven experience in data-driven innovation projects is
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with coding, ideally in Python or MATLAB Funding support This studentship is open to Home students only. It is jointly supported by the Faculty of Engineering and industrial partners which is expected
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or Abaqus (or willingness to learn) General knowledge of structural analysis and material behaviour, especially failure mechanisms Some experience with coding, ideally in Python or MATLAB Funding support This
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-field methods) Multiscale mechanics and microstructure-property relationships Python/C++/Matlab-based simulation and data analysis Industry-facing research and technology transfer You will also benefit
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to research this topic. Interest in laboratory work and basic technical understanding. Fluent written and spoken English. Programming skills in e.g. Python, R, Matlab and Java. Experience in image processing
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will be an advantage if candidates have an interest in optimisation, control and computing systems, model checking, mathematical logic and good programming skills, ideally in MATLAB, Python and/or C/C
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for this position) Experience with programming languages (e.g., Python, MATLAB) and simulation software Excellent academic a dynamic, creative and pioneering professional attitude with a willingness to