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Teaching
The course is structured in two phases: a one-year MRes course followed by a three-year PhD project. The MRes course will include research and transferable skills training aimed at preparing students optimally to carry out an interdisciplinary PhD in sensor technologies for a healthy and sustainable future.
During the MRes course, students are expected to:
- attend the Principles of Sensing course (approximately eight one-hour lectures and eight two-hour practical sessions);
- attend the Machine Learning for Data Intensive Science course (approximately 24 one-hour lectures);
- attend the Responsible Research and Inclusive Innovation in an Uncertain World course (covering topics in entrepreneurship, inclusive innovation, responsible research and scientific communication);
- attend all workshops, seminars and industry talks; and
- successfully conduct three extended projects;
- two individual research mini projects (approximately ten weeks each in Lent and Easter term) and
- the team challenge (approximately twelve weeks during the summer vacation), which is undertaken by the whole cohort working collaboratively.
During the PhD phase, students will carry out full-time research in one or more of the participating departments. The research will be complemented by formal and informal training opportunities, e.g. workshops and seminars.
| One to one supervision | Students’ PhD projects will be carried out in one of the 20 or so participating departments and co-supervised by at least two out of the about 50 PhD supervisors participating in the Sensor CDT. Research work will be supplemented by cohort activities and transferable-skills workshops. Supervisors will provide general academic advice to students, and subject-specific advice relating to the thesis. Students and supervisors normally meet about once a month to discuss progress, but meetings may be more or less frequent depending on the project’s progression. The °Ç¸ç³Ô¹Ï publishes an annual which sets out the University’s expectations regarding supervision. |
|---|---|
| Seminars & classes | MRes: monthly one-hour industry lectures during Michaelmas and Lent terms. MRes and PhD: sensor-related seminars, workshops or skills sessions, approximately one per month. |
| Lectures | MRes: the Principles of Sensing course (approximately 8 hours), the Machine Learning for Data Intensive Science course (approximately 24 hours) and the Responsible Research and Inclusive Innovation in an Uncertain World course (approximately 16 hours) during Michaelmas term. |
| Practicals | MRes: the Principles of Sensing course (approximately 16 hours) during Michaelmas term. MRes and PhD: approximately four workshops throughout the year. |
| Posters and Presentations | MRes: students will present their results from the mini research projects and the team challenge in the form of a report and an oral or poster presentation. PhD: students will present their research outcomes during talks, seminars and workshops in the form of oral and poster presentations. |
| Taught/Research Balance | Predominantly Research |
Placements
During the MRes phase, students will carry out a number of practicals and mini research projects organised by the participating departments. Industrial partners might offer the opportunity for MRes or PhD students to carry out parts of their projects in the industrial partner's research facilities.
Feedback
The students' coursework, reports and presentations will be marked, and the students will receive feedback on their progress through termly online reports. The students will be supervised during their projects and will receive continuous feedback from their project supervisor.
Assessment
Thesis / Dissertation
For students who carry on to the PhD, a thesis must be submitted and will be assessed via an oral examination by two examiners, usually an internal and an external examiner.
The thesis will have to comply with the rules and regulations set out by the department in which the student is registered for their PhD. The typical length of the PhD thesis will be 60,000–65,000 words. A compulsory viva voce examination will follow thesis submission.
Essays
The courses Principles of Sensing and Machine Learning for Data Intensive Science are assessed through a combination of coursework and written examination. The course Responsible Research and Inclusive Innovation in an Uncertain World is assessed through coursework.
Assessment of the projects includes a number of both shorter and longer written assignments:
* the assessment of each research mini-project will include a literature review, and a technical report of up to 7,000 words;
* the assessment of the Team Challenge will include the whole cohort collaborating to write a technical report of up to 20,000 words (for which a single mark will be assigned to the whole cohort);
* the assessment of the Team Challenge will also involve each student writing individually-marked reflective reports of up to 1,000 words.
Written examination
For the MRes, the courses Principles of Sensing and Machine Learning for Data Intensive Science are assessed though a combination of coursework and written examination.
Other
The assessment of the first research mini-project will include producing a scientific poster, and the assessment of the second research mini-project will include an oral presentation. The assessment of the Team Challenge will include every student making an individual progress-update oral presentation, and also contributing to a final group oral presentation.
Students who continue to the PhD are probationary at first, and will have to undertake a first-year assessment. The form of the first-year assessment will depend on the Department in which the PhD research takes place, but will include the submission of a progress report at the end of the first year of the PhD phase (the second year of the overall programme). Progression and registration for the PhD depend on a successful outcome in this assessment.
