Developing, testing, evaluating and implementing evidence-based healthcare in highly complex situations is becoming increasingly important. Our MSc in Applied Health Research will equip you with the skills necessary to develop a career in the health sector or to design, implement and publish healthcare research.
It offers an excellent grounding in applied health research methods, including quantitative and qualitative methodologies, systematic reviews, randomised controlled trials, epidemiology and health economics.
When you join our department you are joining one of the UK's top health services research, health economics and public health research teams. Our world leading experts help improve human health and prevent illness through the analysis and delivery of leading research.
The MSc in Applied Health Research involves a one-year full-time or two-year part-time Masters programme (180 credits). You will take taught modules worth a total of 120 credits. The compulsory modules worth 70 credits are:
-Introduction to Regression Analysis (10 credits)
-Epidemiology (10 credits)
-Randomised Controlled Trials (10 credits)
-Systematic Reviews (10 credits)
-Qualitative Health Research (10 credits)
-Health Economics (10 credits)
-Introduction to Health Statistics (10 credits)
In addition you will choose modules worth 50 credits from the following:
-Health and Social Behaviour (20 credits)
-Health Policy - Principles, Practice and the Evidence Base (10 credits)
-Further Regression Analysis (10 credits)
-Understanding Clinical Statistics (10 credits)
-Measurement in Health and Disease (10 credits)
-Infection and Disease (20 credits)*
-Public Health Foundations in Practice (20 credits)*
-Health Research in Practice (10 credits)
* Please note Applied Health Research students can only take either Infection and Disease or Public Health Foundations and Practice
As the global population exceeds seven billion, the agricultural industry is one of the largest and most vital in the world. However, it is fundamentally unsustainable. The need to produce enough to feed our population, without compromising future generation's' ability to do the same, is becoming ever more important.
This MSc combines cutting-edge theory with the practical, applied skills you'll need to become an effective researcher or industry specialist. Our teaching draws directly from our research, meaning you'll be working with academics who are leading the field. You'll benefit from state-of-the-art facilities and expertise from Department of Biology staff with close links to the Centre for Novel Agricultural Products and the York Environmental Sustainability Institute.
This course is an ideal next step for students with a BSc who are interested in pursuing a career in research or the environmental sector.
-Learn how basic biomedical research is conducted and translated by scientists in one of the UK’s top-ranked biological sciences departments
-Develop the skills to pursue a PhD in biodiversity and ecosystem research or other specialist career paths within the environmental sector, either in the UK or overseas.
-Biodiversity, Ecosystems and Ecology
-Data Analysis and Programming in the Biosciences
-Research, Professional and Team Skills
-Optional modules in topics including Conservation ecology & biodiversity, Environmental microbiology, Plant-Soil Interactions
You will complete an independent study project during the Summer Term, which is designed to give you experience in managing and completing a project in a cutting-edge research context. This is an opportunity to further develop and apply your skills to a current research question, and specialise in a particular area or research technique within biodiversity research.
Most students choose to complete a project in collaboration with an academic supervisor within the University, but you may opt to complete this project as an external placement. You will have full access to our dedicated Masters workspace whilst completing your project.
We will equip students with the key skills of the modern researcher, including critical thinking, data interpretation, statistics, programming, and the written, oral and graphical presentation of scientific data and ideas.