Teaching
Taught material will take a mixture of formats, including traditional lectures and interactive, discussion-based workshops, blending elements of lecturing, hands-on tutorials, with interactive discussions to stimulate active, critical thinking. Students will benefit from building strong cohort connections, fostering a supportive environment that promotes peer-to-peer learning and collaboration.
Course-specific teaching includes approximately 43 hours of lectures covering tumour genomics, germline cancer genetics, genome integrity and DNA repair, cancer cell biology including the tumour microenvironment, stem cells in cancer, tumour initiation, invasion, and metastasis, cellular senescence, signalling pathways in cancer, hormones and metabolism in cancer, tumour immunology, AI across the full spectrum of cancer research and oncology, the evolutionary biology of cancer, cancer epidemiology, the behavioural sciences as applied to cancer, infections and cancer, cancer prevention, screening, and early detection, the role of state-of the-art technologies in cancer early detection, pre-cancerous states, the role of entrepreneurship in driving innovation in cancer research, cancer therapy including an overview of medical, surgical, radiation and immunotherapy, precision cancer medicine, drug discovery and development in cancer including oncology clinical trials.
These will be supplemented with up to 27 hours of linked course-specific hands-on tutorials and interactive discussion workshops that will enable deeper learning in a range of areas including tumour and somatic single-cell and spatial multi-omic profiling, mutational signatures, cancer genetic epidemiology, cancer prevention, screening, and early detection, AI in cancer, physics and imaging technologies in cancer, somatic genomics and tumour evolution, precision cancer medicine, drug development, and clinical trials in oncology.
In addition, students will receive general skills training in Biostatistics and Bioinformatics , covering core applied statistics, data analysis, scientific computing, and effective data visualisation, and a Research Skills Module that will provide a set of key and transferable skills including research ethics, time management, scientific writing, and oral, written and poster presentation skills.
| One to one supervision |
Up to 32 hours per year. During the research project, students will be fully embedded in the research group of their selected supervisor, and will receive ongoing training and research support according to the needs of the student and the project. They will participate in meetings of the research group and have regular meetings with the research project supervisor and other lab members supporting the project. In many cases they will receive ongoing project-specific skills training from researchers who have expertise in the selected field of study. They will also have a termly meeting with one of the course leaders to discuss progress of the research and engagement with the course and teaching material. |
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| Seminars & classes |
Up to 34 hours per year of core biostatistics and bioinformatics training. Up to 8 hours per year of student directed online skills learning through dedicated interactive courses delivered by the University, some linked with interactive follow-up discussions. Students are also encouraged to attend relevant seminars within the Department, School and wider University. |
| Lectures |
Up to 43 hours of core course-specific lectures per year. |
| Practicals |
32-week lab based project. |
| Small group teaching |
Up to 27 hours per year of hands-on practical tutorials and interactive discussion-based workshops (via small or medium group teaching). |
| Journal clubs |
Up to 10 hours per year These sessions will be supported by more experienced researchers from the host department, who will act as facilitators to provide guidance, structure and assurance of integrity, accuracy and quality of discussions. |
| Taught/Research Balance |
Equal Taught/Research
|
Feedback
With the exception of the biostatistics course, feedback will be provided for each assessed element of the course along with the project plan.
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. As well as receiving termly formal feedback reports via the online Postgraduate Feedback and Reporting System.
Assessment
Thesis / Dissertation
The course is divided into three sections, each contributing a third of the final mark:
Sections 2 and 3: Research project
The research project will begin in November and run for 32 weeks, with students expected to spend the majority of their time working on this project.
Students will be given a list of potential projects and supervisors to choose from, and the course will have an assigned advisor to meet with students and guide them through the available projects. Students will be given time and supported in the first 4 weeks of Michaelmas term to meet with supervisors to discuss potential projects, and to develop a research project outline. They will be required to submit a brief project plan prior to beginning work on the project, for approval by the course academic leadership team.
Students will write up the research project as two components:
Section 2: A literature review of the field (max. 5,000 words), providing the background to. and context for, the research project.
Section 3: The project outcomes: aims, methods, results, data analysis, and discussion (max. 5,000 words).
Other
Section 1: Taught material, coursework and presentation skills
Section 1 will be assessed via:
a small biostatistics assessment towards the end of the Michaelmas term,
a multiple-choice question (MCQ) exam comprising one question per lecture, with students attempting all questions (taken just after the Easter term),
a “Perspectives” piece (1,500-2,500 words), comparing 3 contrasting papers in a topical field which will be completed mostly in the Lent term, with a submission deadline around the end of Lent term (due end of Lent term),
an oral seminar-style presentation delivered in the Lent term on a laboratory/analytical method and how it has changed the field (presented end of Lent term),
a poster presentation delivered on the research project (presented at the end of the research project; mid-July).