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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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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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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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, 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
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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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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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of quantum computing and an understanding of challenges of building large-scale systems. Programming skills in Python. A good Bachelor’s Hons degree (2.1 or above or international equivalent) and/or Master’s
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of challenges of building large-scale systems. Programming skills in Python. A good Bachelor’s Hons degree (2.1 or above or international equivalent) and/or Master’s degree in a relevant subject (physics
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in e-learning IT skills, esp. an object-oriented programming language such as C#, Python, or Java Knowledge in: logistics or/and supply chain management or/and transport planning is required Excellent
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) - Knowledge of programming (C/C++/python/MATLAB), CAD software (SolidWorks/Autodesk) and basic electronics - Understanding of physical and chemical principles of/for transduction - Experience building