"This online Masters degree is suitable for those who have general or specialist experience in clinical trials and aims to broaden their role in the design, management, analysis and reporting of clinical trials as well as for those wishing to gain an understanding of trials before moving into this increasingly important field." - Professor Diana Elbourne, Course Director.
The course aims to develop:
- a theoretical and practical understanding of the issues involved in the design, conduct, analysis and interpretation of randomised controlled trials of health interventions.
- skills to scrutinize information, to critically analyse and carry out research, and to communicate effectively.
The London School of Hygiene & Tropical Medicine (LSHTM) is the leading postgraduate medical institution in Europe in the subjects of public health and tropical medicine. Read about the Clinical Trials Unit at LSHTM being shortlisted for a prestigious BMJ Group Award for their role in Crash-2 clinical trial. This demonstrated the life-saving potential of a cheap drug and is up for BMJ Research Paper of the Year.
You study independently, at a time and pace that suits you (subject to some course-specific deadlines) using the comprehensive study materials provided, with support available from academic staff.
Once registered, you will be sent the learning materials for the module(s) you have chosen to study. Clinical Trials module materials are mostly delivered online. These materials will take you through a programme of directed self-study, and indicate how and where you can obtain supplementary study materials and access tutorial support to enhance your studies.
Tutors are allocated to each module and are available to answer queries and promote discussion during the study year (October to May), through the online Virtual Learning Environment.
If you have any questions, please contact our Student Advice Centre.
Computational Mathematics, in particular the physical applied areas and the theory and implementation of numerical methods and algorithms, have wide-ranging applications in both the public and private sectors. More recently, in this era of ubiquitous and cheap computing power, there has been an explosion in the number of problems that require us to understand processes by modelling them, and to use data sets that are large. Thus the subject of Computational Mathematics has become increasingly prominent. Consequently there is high demand also for computational modellers and data scientists. This programme concentrates on the overlap and synergy between these fields.
The programme consists of 120 credits of courses in total during Semesters 1 and 2, followed by a 60 credit dissertation which is completed during the Summer. The courses taken will be dependent on the availability of courses each year which may be subject to change as curriculum develops to reflect a modern degree programme.
The first semester is composed of a combination of compulsory and optional courses. The compulsory courses will build strong applied mathematical and computational foundations. The curriculum is completed with optional courses in related subjects such as statistics and optimization.
The second semester is again composed of a combination of compulsory and optional courses, building on the skills gained in Semester 1. The compulsory courses include Research Skills, which will prepare you for the Summer Dissertation Project. The optional courses cover a wide range of areas including, for example, data science, high performance computing, and related disciplines such as Informatics and Physics.
The 60 credit individual dissertation will take the form of a supervised research-style project on a topic proposed by a staff member of the Applied and Computational Mathematics group. The aim of the project is to provide practical experience and skills for tackling scientific problems which require both computational approaches and mathematical insight. This will include identifying and applying appropriate mathematical and numerical techniques, interpreting the results, and presenting the conclusions.
This programme will provide training in the tools and techniques of mathematical modelling and scientific computing, and will provide students with skills for problem solving using modern techniques of applied mathematics.