102 web-programmer-developer-"https:"-"https:"-"https:"-"https:"-"UCL" positions at Manchester Metropolitan University
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other clinical partners, the new evidence will be rapidly translated to improve local and national prehabilitation programmes that maximise patient engagement and outcomes. Project aims and objectives Aim
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mentoring programmes, accessibility resources, and professional development opportunities to empower and support underrepresented groups. Manchester Met is a Disability Confident Leader and, under this scheme
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, you'll help shape our future technical strategy—keeping our services adaptable, aligned to university priorities, and responsive to sector developments. You'll also represent Manchester Met in external
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accessible AI. Project aims and objectives The aim of this PhD project is to develop principled and efficient methods for multimodal learning under resource constraints. The research seeks to understand how
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International Learning) running across the institution to develop a novel AI-XR prototype. The successful candidate will have the unique opportunity to drive the development of a novel AI-XR curriculum framework
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predict the hair line. Design a classification algorithm to quantify the hair loss severity. Develop a mobile phone app as point of care for people with alopecia. Evaluate novel AI assessments using
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into the organisation's sustainability strategy. What you’ll do: Scope and categorise additive manufacturing waste in F1 motorsport to inform target waste streams with recycling potential. Develop solutions for AM waste as
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-Allah and Dr David Sawtell, which has been developed through a Royal Society Research Grant and a proof-of-concept fund to further investigate new methods for improving the energy efficiency of the plasma
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Manchester School of Digital Arts (SODA). Key Responsibilities Support in the marketing of the university's Creative sub-brands both internally and externally. Support in the development of rich content
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of wind tunnel components in elite motorsport. This interdisciplinary project will develop a data-driven approach to understand and predict how process settings, build orientation, machine variability, and