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(e.g. APMS) with software such as Stata, R, MPLUS, or Python. The successful candidate will contribute to publications, reports and dissemination activities, present findings at seminars, meetings and
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computing paradigms (e.g., MPI, CUDA, etc.); designing and managing new electromagnetic solvers and associated codebases in C++ and/or Python. This is a particularly good opportunity for students who
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available here . Key Accountabilities Research Assistant / Research Associate Support development and documentation of Python-based Design Tool workflow for D-Suite Project Formulate and solve optimization
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
, computer vision, and data analysis using industry-standard tools such as Python, MATLAB, and deep learning frameworks. The student will enhance their ability to manage complex, interdisciplinary research
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Experience Experience developing research software using appropriate languages and environements (Python, Julia, Matlab) Knowledge of optimisation problem formulations and solution methods Experience of risk
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Python with demonstrable familiarity with PyTorch, experience in working on shared codebases, excellent applied math skills (especially probability theory, matrix algebra, calculus). Beyond technical
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-scale job ads datasets, spatial datasets, patents). Conduct data analysis using econometric and statistical tools. Excellent knowledge of R is expected. Good knowledge of Python, experience with modern
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in AI and machine learning – from classical approaches to large language models. You are proficient in Python and key ML libraries (e.g. scikit-learn, PyTorch, LLM APIs), and you have a track record of
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optimisation or machine learning (e.g., Python/Matlab/C++; PyTorch/TensorFlow). Experience in signal processing/wireless or SDR/GPU prototyping is a plus. Demonstrated research potential is highly desirable
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, data analysis, and scientific writing and communication. Experience in working in an optics lab and programming in Python will be beneficial but is not necessary. Applicants should have, or expect