PhD training programme
Future materials chemistry innovators will learn of the many disciplines contributing to it. This includes physical science, computer science, and engineering. They'll become familiar with the multifaceted process of innovation, including value creation and social responsibility. Our students will gain team-working skills, including leadership, key player contributions, and electronic data interchange (EDI) awareness.
The Doctoral Project
Research projects are cross-disciplinary, and co-supervised scientists from academia and industry. Students will start their selected doctoral project immediately after the induction week.
Each project will contain:
- A digital element: robotics, automation, or computer-aided material development (data or computation based)
- A materials chemistry element: synthesis or advanced characterisation methods.
All components will be functional to the achievement of the research objectives.
Technical Training
The key themes of the training are as follows:
- Robotics and automation
- Data science and artificial intelligence (AI)
- Computational materials science
- Sustainability in materials research
- Materials characterisation
- Leadership and value-creation.
They are taught in self-contained modules to enable a clear introduction of fundamental aspects. In later years, applications, masterclasses and case study problems of increasing variety and complexity will enable students to build expertise.
The training will make extensive use of group activities and peer-assisted learning. These are designed for a diverse cohort of students to learn how to communicate across traditional disciplinary boundaries.
Professional & transferable skills (University PGR Development Hub)
Alongside the CDT’s technical training, students can access the University of Liverpool’s PGR Development Hub for an extensive programme of professional and transferable skills. Workshops and resources cover areas such as research communication and writing, project/time management, leadership and teamwork, research integrity and open research, public engagement, data management/digital skills, careers planning and wellbeing. See the PGR Development Hub for details.
Structure of the taught component
Year 1
Robotics & Automation (1): Fundamentals of Robotic Systems & Laboratory Automation; Robotics Software Engineering, Robotics in synthesis, Robotics and AI for Materials Chemistry Winter School
Data Science, AI & Optimisation (1): Statistics; ML Foundations with Applications in Materials Chemistry, Cheminformatics
Computational Materials Science (1): Electronic Structure of Solids, Density Functional Theory and Commonly Used Software
Materials Characterisation (1): Introduction to Solids, Crystallography
Computer Programming: Principles and Applications to Materials Modelling
Introduction to Leadership, Entrepreneurship, Value-creation: Technology Management, Business Planning, Legislation, IP, Ethics
Professional Skills (1): Equality and Diversity at Work, Project Management, Research Data Keeping
Research Engagement: Conference and Presentation Development, Student-Led Seminars & Peer Learning, Cohort Away Days, Research Showcase Events
Project Work: Time dedicated to working on the student’s individual PhD research project
Year 2
Robotics & Automation (2): Automated Characterisation; Intelligent Robotics, Computer Vision, Flow Chemistry, Safety
Data Science, AI & Optimisation (2): Deep Learning, Optimisation, Autonomous Discovery, Natural Language Processing, Geometric Data Science
Computational Materials Science (2): Classical Simulations, High-throughput Virtual Screening, Crystal Structure Prediction
Materials Characterisation (2): NMR, Scattering Methods for Soft Matter, High-throughput, Electron Microscopy
Leadership & Value-creation (2) Regulatory Frameworks, Scaling Up, Supply Chains, Sustainability, Responsible Innovation
Professional Skills (2): Networking, Public Communication of Science, Open Science
Research Engagement: Conference and Presentation Development, Student-Led Seminars & Peer Learning, Cohort Away Days, Research Showcase Events
Project Work: Time dedicated to working on the student’s individual PhD research project
Year 3
Pathways to Automation: Case Studies from UoL Academics and Partners
Digital Intelligence in Action: Applications and Case Studies from Industrial Partners
Computational Methods in Action: Applications and Case Studies from UoL Academics and Partners
Leadership & Value-creation (3) Masterclasses and Case Studies from Partners
Professional Skills (3) Employability & Careers, Cohort Outreach Events
Research Engagement: Conference and Presentation Development, Student-Led Seminars & Peer Learning, Cohort Away Days, Research Showcase Events
Project Work: Time dedicated to working on the student’s individual PhD research project
Year 4
Leadership & Value-creation (3) Masterclasses and Case Studies from Partners
Professional Skills (3) Employability & Careers, Cohort Outreach Events
Research Engagement: Conference and Presentation Development, Student-Led Seminars & Peer Learning, Cohort Away Days, Research Showcase Events
Project Work: Time dedicated to working on the student’s individual PhD research project
Further opportunities for CDT students
The CDT in Digital and Automated Materials Chemistry offers personalised opportunities for students. These include placements with national industry partners or international academic partners. Students have access to specialised training activities and opportunities to present their work at national and international conferences.
Our experienced supervisory pool provides extensive support, complemented by state-of-the-art facilities at the Materials Innovation Factory. This environment nurtures students interested in exploring innovative research paths. Engaging in our cohort experience enhances the excitement and productivity of doctoral studies. Additionally, our strong connections with potential employers and tailored professional training will assist students in achieving their career goals.