Postgraduate Course: Data Science in Clinical Research: Research Proposal (PAMA11082)
Course Outline
| School | Deanery of Clinical Sciences |
College | College of Medicine and Veterinary Medicine |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | The course, along with its co-requisites, is designed to develop the ability to think scientifically and to develop scientific written communication skills. The student will address an individual research challenge by developing a research proposal. Students will complete a literature review that follows expected academic conventions of style, tone, structuring and referencing. They will then develop research questions, understanding appropriate study designs, and developing analytical methods. The research proposal will be written up in the form of a standard grant or fellowship application.
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| Course description |
The types of activity involved in response to a specific research challenge will vary but will include most of the following:
- researching the literature and gathering background information
- analysing and extending relevant theory in novel ways
- analysing requirements, comparing alternatives and specifying a solution
- designing and implementing the solution
- developing written presentation skills
The activity will be supervised by a clinical academic within the University Department of Anaesthesia, Critical Care and Pain (or equivalent) and a co-supervisor with expertise in data science/informatics. We encourage co-supervision from the public sector (e.g. NHS) and industry, from which we anticipate a fruitful supply of appropriately challenging research topics.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
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 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Dissertation/Project Supervision Hours 5,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
191 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Written Exam 0 %
Coursework 100 %
Practical Exam 0 % |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Search and use appropriately databases of scientific literature
- Critically evaluate previous work in the area to structure and summarise a body of knowledge relating to a substantial research topic in data science leading to new hypotheses
- Critically engage with the principles of study design to develop a research proposal for their project from formulation of the research questions to analysis of the results
- Demonstrate a critical understanding of a range of analytical approaches and of the need to select an appropriate approach for answering their research questions
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Literature review,research project,data science,clinical medicine |
Contacts
| Course organiser | Dr Nazir Lone
Tel:
Email: |
Course secretary | Mrs Olga Paterson
Tel: (0131) 242 6130
Email: |
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