Postgraduate Course: Group Research Project (Biomedical AI) (INFR11203)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | In this course you will undertake a group research project in Biomedical Artificial Intelligence under the supervision of a member of staff and/or small supervisory team of staff with experience in Machine Learning & Biomedicine. The project will draw on the new skills and knowledge that you have acquired through other courses and will especially develop your skills and experience in working in an inter-disciplinary research group tackling a common challenge in biomedicine using a range of methodologies. |
| Course description |
In this course we aim to develop your skills in working in inter-disciplinary research teams in which you will have to communicate and work effectively with people from a diverse range of backgrounds. You will learn how to manage your time and partition tasks to allow the group to progress efficiently through the project. Many teamwork elements are involved in working on a joint research project and form an essential part of your training as inter-disciplinary scientists, but the opportunity to share knowledge and skills with peers is of key importance. The project(s) themselves will be proposed by supervisors within the CDT pool of expertise and also external partners who often bring unique datasets and sectorial experience to projects. All project proposals are assessed and approved by the CDT management prior to being presented to students by the supervisory team in a dedicated showcase session.
Throughout the project(s) there will be a focus on developing good scientific practice, including reproducible research methods and incorporating appropriate consideration of any ethical and societal aspects that may be involved. In the final dissertation students will need to demonstrate the ability to accurately present their research in a comprehensive and well-structured document meeting the specifications detailed on the course LEARN website.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | This course is ONLY available to students in the CDT in Biomedical Artificial Intelligence |
Course Delivery Information
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| Academic year 2021/22, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 2,
Seminar/Tutorial Hours 2,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
192 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
100% Coursework
The course assessment will consist of a written report to be marked by the supervisor, and an oral presentation to be assessed by the supervisor and an external member of staff. The dissertation will address the following:
- motivation: why is the problem tackled important?
- background: what are the necessary AI and biomedical knowledge?
- originality: what is different in what is proposed?
- implications: what is the impact of the research, both scientifically and more broadly in terms of its societal implications? |
| Feedback |
Feedback on assessed coursework will be provided within two weeks, and will include formative comments on work in relation to concepts studied in the course.
Report drafts will be reviewed by peers, the course instructor, and individual supervisors under a provided rubric. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Coordinate with a team of diverse experts to answer a research question in biomedical artificial intelligence.
- Plan and monitor a coordinated effort to meet milestones and deadlines within a limited timescale.
- Communicate novel research results in biomedicine and AI to an interdisciplinary scientific audience orally and in writing.
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Additional Information
| Graduate Attributes and Skills |
Students on the course will develop skills in In using a range of specialised skills, techniques, practices and/or materials that are at the forefront of, or informed by forefront developments; In applying a range of standard and specialised research and/or equivalent instruments and techniques of enquiry; planning and executing a significant project of research, investigation or demonstrating originality and/or creativity, including in practices; exercise substantial autonomy and initiative in professional and equivalent activities. |
| Special Arrangements |
This course is ONLY available to students in the CDT in Biomedical Artificial Intelligence |
| Keywords | BAI-IP |
Contacts
| Course organiser | Dr Diego Oyarzun
Tel:
Email: D.Oyarzun@ed.ac.uk |
Course secretary | Ms Lindsay Seal
Tel: (0131 6)50 2701
Email: lindsay.seal@ed.ac.uk |
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