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ACRC Academy

ACRC Academy

We are looking for the next generation of leaders who can transform advanced care.

The vision of the Advanced Care Research Centre is of high‐quality data‐driven, personalised and affordable care that supports the independence, dignity and quality‐of‐life of people in later life living in their own homes and in supported care environments. With fresh and diverse thinking across interdisciplinary perspectives our Academy students will work to creatively embed deep understanding of social sciences, health and social care, engineering, artificial intelligence and data science into systems which support that vision of radically improved care in later life.

Over four years you will study on a thriving, cohort-based, thematic programme with a first year of interdisciplinary training, and continuing training and support throughout the research phase. A wide range of external input ensures that the Academy is fully engaged with real-world challenges and aware of latest development in the field. We have high profile guests and speakers from the fields of medicine, social care and technology, while external placements will mean that students will bring new experience, skills and connections back to their longer-term training and research.

The ACRC Academy will equip future leaders to drive society’s response to the challenges of later life care provision; a problem which is growing in scale, complexity and urgency. Our alumni will become leaders in a diverse range of pioneering and influential roles in the public, private and third sectors.

Who are we looking for?

Candidates should ensure that they fulfil the following eligibility criteria at the time of the call deadline. If it becomes clear during the evaluation phase that one or more of the eligibility criteria have not been fulfilled, the proposal will be withdrawn from any further examination.

  • Candidates must clearly demonstrate a desire and aptitude for a future career in the field of care for those in later life.
  • Candidates must have (or expect to be awarded) at least a 2:1 honours degree or its international equivalent in a relevant subject.
  • Candidates who achieved a 2:2 University Degree or equivalent may be considered if they can demonstrate sufficient relevant work experience at a suitable level
  • Candidates must have an excellent academic record
  • Candidates must evidence a high working knowledge of English (IELTS Level 7 or higher, or equivalent)
  • The call is open to candidates of all nationalities but there are strictly limited places for international students who can apply for the highly competitive ACRC Global Scholarship.

How to apply

For full detail on eligibility and the application process please see How to apply .

ACRC Academy

PhD opportunities

Automatic Affective Behaviour Monitoring through audio-visual information while preserving user’s privacyDetails
Multimorbidity as an index condition for clinical trials, meta-analyses and clinical guidelines - is a paradigm shift needed?Details
Sans everything: sensory loss in the 7th ageDetails
Sleep and delirium - towards a multicomponent intervention to improve sleep on acute medicine of elderly wardsDetails
Elderly patients: tackling neglected tropical disease (NTDs) and living in dignityDetails
Causal data-driven insight and prediction in careDetails
Co-Design of Smart and Data-Driven Health Monitoring Furniture for Care ApplicationsDetails
Development of Next Generation of Near-Infrared Sensors for Advanced Woundcare in Healthy AgeingDetails
Music Listening and TransitionsDetails
Towards a method and system for widespread inexpensive unobtrusive continuous measurement and analysis of tremor as one indicator of frailty in an ageing population.Details
Experience and outcomes of persistent delirium for individuals and family carers post discharge from acute hospital careDetails
Neighbourhood and health in later life: a mixed methods studyDetails
Spirituality, wellbeing, and careDetails
Developing new approaches to participatory design for advanced care technologies in later lifeDetails
Understanding and clustering trajectories of multimorbidity using interpretable machine learningDetails
Governance for Trusted Integrated Care InfrastructureDetails
Independence in the 'Elder Experience'Details
Identifying and resolving the ethical challenges of the use of AI and robotics in supporting elderly people in the communityDetails

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