The MCh enables experienced, qualified doctors to develop an evidence- based approach to health care practice and to obtain a postgraduate qualification whilst enhancing their surgical clinical expertise within the NHS.
The programme has been designed in collaboration with senior surgeons and academics and is at the cutting edge of both contemporary surgical practice and research. It will allow you to extend your knowledge and skills to advanced levels within your specialist area of work. The clinical modules focus on practical skills in operative surgery with the use of interactive teaching aids and practical workshops.
You can choose from eighteen established specialist pathways or pursue a generic MCh Surgery pathway which offers the potential to develop expertise in an alternative relevant sub-speciality.
*Pathways currently accredited by the Royal College of Surgeons (England).
Whichever pathway you choose, the programme will be delivered in partnership with Wrightington, Wigan and Leigh NHS Foundation Trust. Wrightington Hospital is recognised as a Centre of Excellence (Orthopaedic Surgery) and has clinical facilities / laboratories that will provide you with excellent learning opportunities.
This programme consists of three distinct 20 credit clinical modules, two 30 credit clinical research modules and a 60 credit dissertation. Topics covered will include: Specialist aspects of evidence based practice in surgery; Qualitative and quantitative research methods; Critiquing research findings; Writing a research proposal; Analysis of quantitative data; Systematic reviews; Research governance and ethics; Focus on a significant piece of investigative enquiry from conceptualisation through to completion.
The programme is delivered over two to three years, commencing in September each year. The academic year runs from September through to July, though the dissertation submission will be in September of the second year, with the option to defer the dissertation to the third year. You will experience a variety of teaching and learning strategies including lectures, seminars, individual and group tutorials and independent guided study.
An online Virtual Learning Environment (VLE) is used for some components of the programme. The surgical modules have elements of practice-based learning and involve the completion of a log of practical experience which complements the course material. The dissertation allows you to focus on a significant piece of investigative enquiry from conceptualisation through to completion.
Assessment methods include a research proposal, written assignments, completion of online activities and discussions, Objective Structured Clinical Examinations (OSCEs), clinical log books, seminar presentations and a dissertation.
The programme team consists of experienced academic staff from across Edge Hill University and expert clinicians from Wrightington Hospital. This collaborative approach provides a team of high calibre individuals to support your learning. Additionally, leading surgeons from related specialities are invited as guest speakers on the surgical modules. Edge Hill University enjoys an excellent reputation for the teaching quality of its programmes. All staff involved in the delivery of modules and pathways within this programme are currently involved in scholarly and research related activities which are congruent with their teaching responsibilities.
Medical professionals need to continually seek ways to improve their career prospects in an increasingly competitive job market where a postgraduate qualification is often now deemed essential.
The MCh provides a highly relevant qualification for doctors working in a specialist area of surgical practice which will add to your portfolio of qualifications and provide you with opportunities for professional development supported by expert clinicians and academics.
This two-year part-time masters programme, taught entirely online, is offered by the Royal College of Surgeons of Edinburgh and the University of Edinburgh, and leads to the degree of Master of Surgery (ChM).
Based on the UK Intercollegiate Surgical Curriculum, it provides the opportunity for trainees in urology to select those advanced modules relevant to their declared specialty and supports learning for the Fellowship of the Royal College of Surgeons (FRCS) examinations.
The programme is designed to run alongside clinical training and complement in-the-workplace assessment.
Our online learning technology is fully interactive, award-winning and enables you to communicate with our highly qualified teaching staff from the comfort of your own home or workplace.
Our online students not only have access to Edinburgh’s excellent resources, but also become part of a supportive online community, bringing together students and tutors from around the world.
The programme runs on a semester basis over two years and involves approximately 10 hours of study each week, in a flexible modular manner. It is anticipated that some of this study would receive credit or mirror 'in-the-workplace' activities.
The online distance learning nature of this programme is perfect for doctors working unsociable shift patterns. You will have access to high-quality, interactive online resources, e-journals and online textbooks, as well as dedicated technological support.
Compulsory modules will cover the basic elements of the specialty of urology, including oncology, andrology, stone disease, reconstructive urology, paediatric urology and renal transplantation. Each module is based around relevant surgical cases and includes discussion board and video master classes.
Academic modules will explore research and teaching methodology, whilst enabling students to develop the ability to analyse published evidence and enhance their interactive and written clinical communication skills. Students will also have the opportunity to complete an academic research project in Year 2 e.g. Original research or a Systematic Review in a relevant area of work. Following completion of the programme, students are encouraged to seek publication of their study in a peer-reviewed journal.
Students are supported throughout the programme through asynchronous discussions with e-tutors who are all leading clinicians in their field. Students also have access to a large learning resource, including subscriptions to key online books and journals. A written examination (MCQ) is held in the second year, following completion of core modules.
Graduates will be able to demonstrate in-depth knowledge of their chosen surgical subspecialty and to apply this knowledge to the systematic assessment and management of surgical patients in the elective, urgent and emergency clinical setting.
* One-year masters studentships are available for this stream. Each studentship will be worth £5000 and can be taken either as a reduction in fees or as a bursary. Studentships will be awarded based on academic merit and are open to all applicants, regardless of fee status (home/EU/overseas). Please indicate 'Data Science' in the first line of your personal statement.
* Two PhD Studentships targeted at successful graduates from this stream. Two 3-year PhD studentships will be on offer, targeted at students obtaining a minimum of a Pass with Merit on the Data Science stream. These studentships will cover the cost of tuition fees for home/EU applicants and a stipend at standard Research Council rates.
This course is a stream within the broader MRes in Biomedical Research.
The Data Science stream provides an interdisciplinary training in analysis of ‘big data’ from modern high throughput biomolecular studies. This is achieved through a core training in multivariate statistics, chemometrics and machine learning methods, along with research experience in the development and application of these methods to real world biomedical studies. There is an emphasis on handling large-scale data from molecular phenotyping techniques such as metabolic profiling and related genomics approaches. Like the other MRes streams, this course exposes students to the latest developments in the field through two mini-research projects of 20 weeks each, supplemented by lectures, workshops and journal clubs. The stream is based in the Division of Computational and Systems Medicine and benefits from close links with large facilities such as the MRC-NIHR National Phenome Centre, the MRC Clinical Phenotyping Centre and the Centre for Systems Oncology. The Data Science stream is developed in collaboration with Imperial’s Data Science Institute.
Students with a degree in physical sciences, engineering, mathematics computer science (or related area) who wish to apply their numeric skills to solve biomedical problems with big data.
Students will gain experience in analysing and modelling big data from technologically advanced techniques applied to biomedical questions. Individuals who successfully complete the course will have developed the ability to:
• Perform novel computational informatics research and exercise critical scientific thought in the interpretation of results.
• Implement and apply sophisticated statistical and machine learning techniques in the interrogation of large and complex
biomedical data sets.
• Understand the cutting edge technologies used to conduct molecular phenotyping studies on a large scale.
• Interpret and present complex scientific data from multiple sources.
• Mine the scientific literature for relevant information and develop research plans.
• Write a grant application, through the taught grant-writing exercise common to all MRes streams.
• Write and defend research reports through writing, poster presentations and seminars.
• Exercise a range of transferable skills by taking short courses taught through the Graduate School and the core programme of the
MRes Biomedical Research degree.
A wide range of research projects is made available to students twice a year. The projects available to each student are determined by their stream. Students may have access from other streams, but have priority only on projects offered by their own stream. Example projects for Data Science include (but are not limited to):
• Integration of Multi-Platform Metabolic Profiling Data With Application to Subclinical Atherosclerosis Detection
• What Makes a Biological Pathway Useful? Investigating Pathway Robustness
• Bioinformatics for mass spectrometry imaging in augmented systems histology
• Processing of 3D imaging hyperspectral datasets for explorative analysis of tumour heterogeneity
• Fusion of molecular and clinical phenotypes to predict patient mortality
• 4-dimensional visualization of high throughput molecular data for surgical diagnostics
• Modelling short but highly multivariate time series in metabolomics and genomics
• Searching for the needle in the haystack: statistically enhanced pattern detection in high resolution molecular spectra
Visit the MRes in Biomedical Research (Data Science) page on the Imperial College London web site for more details!