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of command-line tools, Python, or R for data analysis is a significant advantage. Language: Proficiency in English (written and spoken) is mandatory, as this is an international collaboration project. French
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Experience and practical knowledge of programming languages and tools (e.g. Python, Java, etc.) Knowledge in Software Engineering, AI, machine learning is an advantage Experience with software observability
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programming skills (e.g., Python, MATLAB) would be desirable but are not essential. How to apply Interested applicants should contact Prof Tom Coulthard (T.Coulthard@mmu.ac.uk ) for an informal discussion
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analysis and at least one programming language (e.g. R, Python, MATLAB); Interest in sustainability and evidence-based environmental research. Desirable Knowledge of ecological survey design and biodiversity
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analysis software (e.g., Fiji/ImageJ). Advanced Cell Manipulation (e.g., genome editing via CRISPR/Cas9, flow cytometry/FACS). Basic familiarity with data analysis tools (e.g., GraphPad Prism, R, or Python
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level. Background in solid-sate physics, semiconductor devices, quantum information, and/or analogue circuits is desirable. Experience in data analysis and programming, particularly in the use of Python
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/PYTHON/R/C programming • Application of Machine Learning Algorithms Additional Information Benefits This scholarship covers the full cost of tuition fees, an annual stipend at UKRI rate (currently
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culture and in vitro models of mucosal immunity Data analysis using Python and digital image processing These skills are highly transferable to careers in biomedical research, pharmaceutical development
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partners. Training & environment You’ll gain deep skills in hypersonic flows, AI for PDEs, data assimilation, and reproducible HPC workflows (Python/C++/PyTorch/JAX). You’ll be supported with paper writing
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and interest in working with custom-built or modified instruments Solid programming skills (e.g. Python) are desirable Ability to work independently and self-reliantly, while maintaining strong teamwork