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the development and validation of multi-scale fracture mechanics models. In this role, you will bridge numerical simulation with physical experiment, developing automated Python workflows, running
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can derive by hand and build up to large-scale calculations. You will need a background in condensed matter physics / quantum mechanics and an interest in coding (Python); no prior experience with
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PhD. Be able to commence the Program in the year of the offer. The ideal PhD candidate will have: A strong background in machine learning, deep learning, and software programming Proficiency in Python
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Required knowledge Skills Focus proficiency in one programming language (e.g. Matlab, R, Python), machine learning / deep learning / data science skills, basic understanding of cell and development
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of the offer. The ideal PhD candidate will have: A strong background in machine learning, deep learning, and software programming Proficiency in Python and machine learning frameworks such as PyTorch
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have: A strong background in software security, linear algebra and software engineering Proficiency in Python and machine learning frameworks such as PyTorch (required) Knowledge of quantum computing
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learning, and software programming Proficiency in Python and machine learning frameworks such as PyTorch (required) Knowledge of quantum computing or quantum algorithms (advantageous but not essential
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. You’ll bring strong technical capability across data extraction and transformation, visualisation, database querying and automation, with experience using tools such as Python and process mapping software
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Python, Flask, Docker, AWS, and GitLab. AI & Computer Vision Experience: Proven experience with computer vision systems, machine learning workflows, MLOps, and edge processing optimisation. Multimodal
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related field. Strong analytical and manuscript preparation skills, experience analysing complex clinical or biological datasets and the ability to develop well-documented code in R, Python or another