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tools, collaboration with project stakeholders, and engagement with the consortium and Defence and Security stakeholders. Technical Requirements: Strong coding skills with background in machine learning
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blow moulding. You will also have: Experience applying AI or coding tools (e.g. Python or MATLAB) to analyse scientific data A track record of conducting and interpreting experimental work The ability
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blow moulding. You will also have: Experience applying AI or coding tools (e.g. Python or MATLAB) to analyse scientific data A track record of conducting and interpreting experimental work The ability
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research experience. Proven track-record analysing large-scale ‘omics and/or healthcare datasets, preferably in cancer genomics. Experience of advanced coding in Python or R plus Shell scripting; familiarity
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of Birmingham is inviting applications for a Research Fellow position focused on Machine Learning for Automated Formal Verification. Machine learning has transformed programming, with code generation rapidly
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practices in code development and maintenance (e.g. Github/Gitlab, GitHub Actions, etc). Experience with machine learning or network-based approaches is desirable. Familiarity with FAIR data principles and
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will develop and apply methods to transform omics data into networks and executable models, collaborating closely with experts across the Petsalaki and Sheriff groups, Open Targets, EMBL-EBI, and the
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practices in code development and maintenance (e.g. Github/Gitlab, GitHub Actions, etc). Experience with machine learning or network-based approaches is desirable. Familiarity with FAIR data principles and
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with a wider interdisciplinary research team Participate in wider networks, including the Adult Social Care Cluster and DEMCOMM programme events Main Duties The responsibilities may include some but not
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ongoing development of communication updates for web, social media and networking Promote equality and value diversity, acting as a role model and fostering an inclusive working culture Support the work