Teaching
Our curriculum focuses on the cutting-edge intersection of neuroscience and artificial intelligence, equipping you with valuable knowledge and transferable skills that will empower you throughout your academic and professional journey.
The core of our teaching consists of approximately 60 hours of specialised lectures on current topics in NeuroAI and Intelligent Systems. These lectures cover a wide range of areas, including neural computation, connectionist theory, dynamical systems, state-of-the-art topics like transformers and state-space models, as well as technical seminars. The course also features guest lectures from industry and academic leaders in the field of NeuroAI.
Additionally, you'll select approximately 30 hours of complementary content from existing courses at the MRC Cognition and Brain Sciences Unit. Options include the Cognition and the Brain course (covering cognitive theory and systems neuroscience) and Human Neuroimaging training (covering techniques such as magnetic resonance imaging, brain stimulation techniques, and various types of brain modelling). The technical components will be delivered through a mix of formats, emphasising small group work and interactive learning to stimulate active critical thinking.
Journal club presentations and discussions will form an important part of the course, where you'll contribute to selecting topics focused on research papers and state-of-the-art techniques. These sessions will be facilitated by experienced researchers who will provide guidance and ensure the quality of discussions.
The taught material will be thoughtfully structured, with content front-loaded into Michaelmas term to establish a solid foundation before you embark on your 32-week research project. Additional course elements will be delivered through weekly sessions throughout the year, ensuring a steady flow of knowledge and engagement.
| One to one supervision |
Up to 32 hours per year |
|---|---|
| Lectures |
Up to 90 hours per year (combining the 60 hours of course-specific teaching in NeuroAI with approximately 30 hours from Cognition and the Brain or Neuroimaging) |
| Small group teaching |
Up to 60 hours per year |
| Journal clubs |
At least 10 hours per year |
| Taught/Research Balance |
Predominantly Taught
|
Feedback
Students will have a termly meeting with one of the course directors, and direct feedback from their research supervisor during their 32 week research project. In the third term they will receive feedback on their poster presentation and dissertation.
Assessment
Thesis / Dissertation
The assessment structure for the course is divided into three parts:
Section 2: Research project literature review (30% of your mark)
You will undertake a comprehensive literature review related to your research project. This review, with a maximum word limit of 5,000 words, will serve as a foundation for your research project, providing essential background information and contextualising the significance of your chosen area of study. Your literature review will be assessed based on the depth of your research, critical analysis, and ability to synthesise and present information effectively.
Section 3: Research project methods and outcomes (40% of your mark)
You will focus on presenting the outcomes of your research project. This component will require you to articulate the aims, methods, results, data analysis, and discussion of your project within a maximum word limit of 5,000 words. You will showcase your research skills, analytical thinking and ability to draw meaningful conclusions from your data.
Essays
Section 1: Extended essay and codebook (30% of your mark)
You will produce an extended essay (up to 5,000 words) introducing and discussing a particular approach within NeuroAI. This will be accompanied by a codebook demonstrating an implementation of the technical approach applied to a dataset or simulated task-design. The assessment includes an in-person viva where you'll discuss your work and demonstrate your understanding of the code. Two markers will assess these components to ensure parity of standards.
Other
These assessments allow you to demonstrate your academic abilities and provide an opportunity for you to contribute to the emerging field of NeuroAI. All sections will be evaluated by experienced faculty members who will assess your work based on its quality, originality and scientific rigor.
By employing this multimodal assessment approach, we aim to evaluate not only your knowledge and understanding but also your critical thinking abilities, research capabilities, and technical skills. This assessment framework ensures that your progress and development as a NeuroAI researcher are effectively recognised. We are committed to providing you with constructive feedback and support throughout your journey, enabling you to grow and excel in this exciting interdisciplinary field.