Training

Training Details

Training and Professional Development

You will experience a valuable and varied research journey. The degree programme aims to ensure that PhD Researchers coming from diverse disciplines gain the interdisciplinary skills needed for Citizen-Centred AI over the course of 4 years. Throughout your research and learning journey you will be supported by two Research Software Engineers working in AI. Training will be tailored to your individual needs with some training compulsory and others optional based on your existing skills.

Year 1

PhD Researchers will undergo training in the computational foundations of AI (semester 1), Human-Centred and Inclusive design (semester 2) and the regulation and governance of AI (semester 3). Everyone will undergo group projects, some of which will be in collaboration with the centre’s public, third sector and business partners bringing in experiential learning from the onset.

Years 2-4

PhD Researchers will pursue their independent doctoral research in collaboration with supervisors with expertise in the topic of research and who match and/or complement each individual’s skill set.

A weekly seminar series will be dedicated for PhD Researchers, supervisors, and partners to engage with continuously evolving AI landscape as well as bring to the fore often marginalised understandings of AI including but not limited to queer, feminist, more-than-human and decolonial theories.

During their degree studies the PhD Researchers will be supported to undertake placements at one of the Centre’s partner organisations and will undergo professional development training to ensure that they work towards their individual career aspirations whether it be in academia or industry.

Seminar Series

As part of our training programme, we will be running a weekly seminar series. The seminar series aims to:

Introduce HCI, Digital Civics and Design theories, concepts, and methodologies that are conducive of meaningfully engaging with citizens, communities, organisations and publics in the design, development and evaluation of AI technologies
Provide a space to explore relevant and emerging topics related to AI technologies and their introduction into society. Topics covered will include but are not limited to Feminist AI, Queering AI, Decolonial AI, More-than-Human AI and Crip AI to name a few. We will also be covering topics related to Responsible AI and AI governance and regulation.

The series will include guest talks by critical and leading voices and researchers, through which we will unpack, sit with and work through the complexities at the intersection of AI and Society. Some of the guest talks will be open to the public, thus engaging the wider CDT community and partners and those external to the CDT in these topical and critical conversations.

Training Timeline

Year One

Students will work in cohorts to undertake core skills training and conduct group research projects aligned with external partners.

Interdisciplinary Skills: Compulsory modules in AI & Machine Learning, Design Methods, Research Methods, Ethics & AI.
Optional Modules: Identified based on individual student’s needs.
Showcase and Summer School: Annual research and training event with external stakeholders.
Annual Progression and Development Needs Analysis: A review and goal setting session for the final year of study.
Group Projects: Students will work in groups on live projects with external stakeholders.
Doctoral Project: Pursue independent doctoral research in collaboration with supervisory team and external partners.
Professional Development: Training throughout the PhD to advance career aspirations.
Seminar Series: Weekly seminar to engage with continuously evolving AI landscape.

Year Two

Students will pursue their independent doctoral research in collaboration with supervisors and external partners.

Personal Development: Additional bespoke training based on individual student’s needs.
Showcase and Summer School: Annual research and training event with external stakeholders.
Annual Progression and Development Needs Analysis: A review and goal setting session for the final year of study.
Placements: Experiential learning at one of the Centre’s partner organisations.
Group Projects: Students will work in groups on live projects with external stakeholders.
Doctoral Project: Pursue independent doctoral research in collaboration with supervisory team and external partners.
Professional Development: Training throughout the PhD to advance career aspirations.
Seminar Series: Weekly seminar to engage with continuously evolving AI landscape.

Year Three

Students will continue with their independent research projects and extend their experience of working with supervisors, peers, and external partners.

Showcase and Summer School: Annual research and training event with external stakeholders.
Annual Progression and Development Needs Analysis: A review and goal setting session for the final year of study.
Placements: Experiential learning at one of the Centre’s partner organisations.

Year Four

In their final year, students will complete their independent research and undertake further career development.

Further Career Development: Individually tailored career training including advanced Soft Skills development.
Showcase and Summer School: Annual research and training event with external stakeholders.
Annual Progression and Development Needs Analysis: A review and goal setting session for the final year of study.
Placements: Experiential learning at one of the Centre’s partner organisations.
Doctoral Project: Pursue independent doctoral research in collaboration with supervisory team and external partners.
Professional Development: Training throughout the PhD to advance career aspirations.
Seminar Series: Weekly seminar to engage with continuously evolving AI landscape.