2022/23 Taught Postgraduate Programme Catalogue
|Programme code:||MOR-NEUROSCI||UCAS code:|
|Duration:||12 Months||Method of Attendance:||Full Time|
|Programme manager:||Dr Samit Chakrabarty||Contact address:||S.Chakrabarty@leeds.ac.uk|
Total credits: 180
BSc 1st class or 2i, or equivalent (for example a pass in MBChB, BDS), in a relevant scientific discipline, normally biological or biomedical sciences, but a natural sciences or engineering graduate will be considered subject to evidence of biological knowledge at an appropriate level.
English language requirement: IELTS 6.5 overall, with no less than 6.0 in in any single component. Alternative English language requirements that are acceptable are:
- TOEFL (Test of English as a Foreign Language) of 92 with no less than 21 in listening, 21 in reading, 23 in speaking and 22 in writing;
- Pearson (Academic) of 64 overall with no less than 60 in any component;
- Cambridge Advanced English (CAE) of 176 overall with no less than 169 in any component;
- Trinity College Integrated Skills in English of a Pass in ISE II or above (if taken in the UK).
School/Unit responsible for the parenting of students and programme:
Biological Sciences Masters (Biomedical Sciences)
Examination board through which the programme will be considered:
Biomedical Sciences Masters Exam Board
Relevant QAA Subject Benchmark Groups:
Subject benchmark statements for biomedical/ biological sciences Masters programmes do not exist.
However, students will be expected to demonstrate the characteristics embodied in the QAA Qualifications Frameworks level descriptors for Masters degrees (https://www.qaa.ac.uk/docs/qaa/quality-code/master's-degree-characteristics-statement.pdf?sfvrsn=6ca2f981_10).
The programme is designed to train students to be ready to begin work as PhD students or as junior research assistants if working in an academic or industrial environment. So, the course is designed such that the students at the end of the course can do the following.
- Develop an understanding of normal neurological function in vertebrates to enable better understanding of dysfunction;
- Use of technologies to interrogate the neurological dysfunctions in the vertebrate population (animal and human diseases);
- Design, conduct experiments and research projects to better the neuronal systems;
- Analyse the data using appropriate methods and statistical techniques, and interpret, critically discuss and draw conclusions from these data;
- Establish efficacious use of new tools and their outcome evaluation to enable easy transfer of knowledge to preclinical and clinical scientists;
- Provide insight into how this information can then be transferred towards drug discovery, diagnostics, biomarker screening for patient stratification, improved rehabilitation and technological adaptations;
- Introduce use of big data analysis, use of mathematical algorithms and software pertinent to study of the nervous system and development of new tools involving capture of biological data, processing and its use for producing a define output.
The programme will begin by giving students an overview of the field of neuroscience and use of advanced tools and techniques useful in interrogating it for preclinical and clinical purposes. With an emphasis on neurotechnology, this becomes even more relevant. Students will learn about the data analysis tools and fundamentals of bioimaging, both of which will be using data from real experimental scenarios. They will be taught the use of core statistical models (classification, regressions), for analysis of different time-series datasets provided by the local researchers (EMGs, EEGs, continuous visual images, animal and human locomotion, etc). These will enable the students to analyse and interpret the large scale biological and biomedical data for physiological markers. They will be provided with the basics of use of algorithms towards solving complex problems like diagnosis of function or improved function with therapies.
Students will be introduced to the field of neurotechnology, pain medicine, real-time data processing for analysis of motor control, analysis of data and design of experiments to understand the underlying biological mechanisms but using physical and mathematical tools.
Year1 - View timetable
[Learning Outcomes, Transferable (Key) Skills, Assessment]
Candidates will be required to study the following compulsory modules:
|BMSC5125M||Advanced Data Analysis Techniques|
Pre-requisite for: BMSC5395M
|15 credits||Semester 1 (Sep to Jan)|
|BMSC5301M||Advanced Research Topics|
Pre-requisite for: BMSC5395M
|30 credits||Semester 1 (Sep to Jan)|
|BMSC5395M||MRes Research Project||120 credits||Semesters 1 & 2 (Sep to Jun)|
Candidates will be required to select one of the following optional modules:
|BIOL5312M||Bioimaging||15 credits||Semesters 1 & 2 (Sep to Jun)|
|SPSC5126M||Motor Control and Neurorehabilitation||15 credits||Semester 1 (Sep to Jan)|
Last updated: 29/04/2022 15:48:28
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