20 coding-"https:"-"https:"-"https:"-"Computer-Vision-Center" Fellowship positions at University of Birmingham
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Job Description Position Details School of Computer Science Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally in the range £36,636 to £46,049 with
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computer vision. The successful candidate will actively participate in the Co-AIMS mission to drive impactful research in the context of research priority area of Adaptive Skill Learning and Human-AI
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will work on “bcc-superalloys” ( https://doi.org/10.1016/j.scriptamat.2025.116761 ) to achieve top scientific outputs (e.g. Ti https://doi.org/10.1016/j.scriptamat.2017.06.038 , W https://doi.org
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all of these can be found on the MOBILITY website ( https://www.birmingham.ac.uk/about/college-of-medicine-and-health/research-office/fellowship-academy-for-medicine-and-health/mobility ). Please also
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research methods, such as literature reviews and research interviews Work with research nurses in participating sites to recruit patients to the study Play a key role in coding and analysing research data
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, and analysing, flow cytometry and immunohistochemistry data Previous use of bioinformatic/coding programmes (e.g. R) to generate figures and novel data analysis pipelines. High level analytical
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full details on how to apply and for the required documents you will need to upload as part of your application . https://www.birmingham.ac.uk/about/college-of-medicine-and-health/research-office
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Experience developing & applying machine learning models to computer vision tasks Practical experience in computing languages (python, JAVA script, C++) & deep learning Technical expertise (e.g., adapting
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systems use different data structures, coding systems and identifiers, including SNOMED CT, ICD-10 and OPCS-4. Transforming these routinely collected data into a common data model would enable
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enabling a sustainable and equitable transition in energy and transport systems (see: https://www.cleets-global-center.org/). In the UK, the research is funded by UK Research and Innovation (UKRI