Scholarships available, see Fees & Funding section for more information. The Applied Statistical Modelling and Health Informatics course has been created to deliver a skill set and knowledge base in “multimodal” and “big data” analysis techniques, which are a recognised scarcity within UK Life sciences. You will receive world-class training in core applied statistical methodology, machine learning and computational methodology, and you will have the opportunity to apply your skills to real-life settings facilitated by the world-leading Institute of Psychiatry, Psychology & Neuroscience. The course will apply to a broad spectrum of graduates preparing for a career in medical statistics and health informatics, or professional methodologists and clinical researchers working in the private or public health sector who are interested in state-of-the-art technologies training from world-class experts. This course is also suitable if you are a graduate in/work in the fields of psychology, medical/health sciences, bioinformatics, data science, statistics, maths, physics, engineering and natural science, The course will prepare participants for the ever-growing need for a sound scientific approach to processing information and generating knowledge in modern health services. Practical skills will be taught through applications to real-life settings in a world-leading research institution in mental health.
Our course is to meet the growing need for a graduate training course that focuses on methodological skills to respond to problems of “big data” of complexes diseases, which is underpinned by strong statistical methodology and real-world application.” There is an increasing demand for the acquisition, storage, retrieval and use of information within private and public sector institutions engaged in health research. The range of modern medical data is vast, from patient records, genetics, other omics and imaging data to real-time measures of physiological responses from wearable sensors, smartphone social media use and environmental data. We will provide you with the necessary state-of-the-art statistical modelling and health informatics techniques to manage and evaluate this data. You will receive training in key methodological techniques underpinning “big data” acquisition, information retrieval and analysis using prediction modelling and theory-driven analyses approaches. You will benefit from the teaching of world-renowned experts in the field, you will conduct an applied research project and link to statistical and health informatics research groups, such as the Causal Analysis and Evaluation, Precision Medicine and Statistical Learning, Psychometrics and Measurement Lab, Structural Equation Modelling group, Precision Health Informatics Data Lab and Natural Language Processing groups in the Department of Biostatistics and Health Informatics. You will be part of a multi-professional cohort, bringing together diverse points of view on national and international modern data dilemmas. You will also have the unique opportunity to network and develop career opportunities. Our course combines training in core statistical modelling, health informatics and computational methodology, beginning at an introductory level, with a range of optional modules. The course uses a blended design to teaching and learning, where students access pre-recorded lectures from world’s leading experts, complemented by face to face workshops and seminars to ensure students have a rich and exciting learning experience from the start.
Home to the Institute of Psychiatry, Psychology & Neuroscience.
Please note that locations are determined by where each module is taught and may vary depending on the modules you study.
King's is regulated by the Office for Students
A minimum 2:1 undergraduate Bachelor’s (honours) degree
If you have a lower degree classification, or a degree in an unrelated subject, your application may be considered if you can demonstrate significant relevant work experience, or offer a related graduate qualification (such as a Masters or PGDip).
A bachelor’s degree with 2:1 honours in Computer Science, Mathematics, Statistics, Physics, Natural Sciences, Electronic Engineering, Psychology or Geographic Information Systems. In order to meet the academic entry requirements for this programme you should have a minimum 2:1 undergraduate degree, if you are still studying you should be achieving an average of at least 60% or above in the UK marking scheme.
Other degrees or professional qualifications may be acceptable, such as the Graduate diploma of the Royal Statistical Society.
To study at King's, it is essential that you can communicate in English effectively in an academic environment. You are usually required to provide certification of your competence in English before starting your studies.
Nationals of majority English speaking countries (as defined by the UKVI) who have permanently resided in this country are not usually required to complete an additional English language test. This is also the case for applicants who have successfully completed an undergraduate degree (of at least three years duration), a postgraduate taught degree (of at least one year), or a PhD in a majority English speaking country (as defined by the UKVI) within five years of the course start date.
For information on our English language requirements and whether you need to complete an English language test, please see our English Language requirements page.
Applications must be made online using King’s online application portal apply.kcl.ac.uk and a non-refundable application fee of £85 applies.
Selection is made on the basis of application and references. Potential students are welcome to visit the department: please arrange a suitable time in advance.
You will be asked to submit the following documents in order for your application to be considered:
| Personal Statement | Yes |
Q1. Why are you applying for this specific programme, and how does it fit in with your future plans? Q2. How does your educational background or professional experience make you a suitable candidate for the programme? Q3. Describe a project where you applied statistical or analytical methods, either in an academic or professional setting. What was your role, and which statistical packages, programming languages, or research techniques did you use in this project? If you have limited experience, describe any relevant coursework, self-directed learning, or projects demonstrating your interest and skills in these areas. |
|---|---|---|
| Previous Academic Study | Yes | A copy (or copies) of your official academic transcript(s), showing the subjects studied and marks obtained. If you have already completed your degree, copies of your official degree certificate will also be required. Applicants with academic documents issued in a language other than English, will need to submit both the original and official translation of their documents. |
| References | Yes | One academic reference is required. A professional reference will be accepted if you have completed your qualifications over five years ago. |
| Other | Optional | You may wish to include a CV (Resume) or evidence of professional registration as part of your application. |
Our course combines training in core statistical modelling, health informatics and computational methodology, beginning at an introductory level, with a range of optional modules.
The course uses a blended design to teaching and learning, where students access pre-recorded lectures from world’s leading experts, complemented by face to face workshops and seminars to ensure students have a rich and exciting learning experience from the start.
Each year you will take:
The course uses a blended design to teaching and learning, where students access pre-recorded lectures from world’s leading experts, complemented by face to face workshops and seminars to ensure students have a rich and exciting learning experience from the start.
Teaching
You will be taught through a mix of pre-recorded lectures, tutorials, seminars and digital activities.
| Module name | Lectures (hours) | Seminars/tutorials (hours) | Self-directed study (hours) | Total (hours) |
| Introduction to Statistical Modelling | 40 | 60 | 200 | 300 |
| Introduction to Health Informatics | 20 | 30 | 100 | 150 |
| Multilevel and Longitudinal Modelling | 20 | 30 | 100 | 150 |
| Prediction Modelling | 20 | 30 | 100 | 150 |
| Causal Modelling and Evaluation | 20 | 30 | 100 | 150 |
| Machine Learning for Health and Bioinformatics | 20 | 30 | 100 | 150 |
| Clinical trials: A practical approach | 20 | 30 | 100 | 150 |
| Natural Language Processing (NLP) | 20 | 30 | 100 | 150 |
| Latent Variable and Structural Equation Modelling | 20 | 30 | 100 | 150 |
| Artificial Intelligence for Healthcare Analytics | 20 | 30 | 100 |
150 |
| ASMHI Research Project | 0 | 60 | 540 |
600 |
Typically, one credit equates to 10 hours of work.
Location
Our course is primarily taught on campus at the King’s College London Denmark Hill Campus.
The primary methods of assessment for this course are written examinations, coursework and an e- portfolio of competencies and skills, to support your employability and development. The study time and assessment methods typically give an indication of what to expect. However, these may vary depending upon the modules.
For the full MSc each student will need to complete the ASMHI Research Project module, where assessment will be made up of a dissertation/research report and a poster/viva.
Regulating body
King’s College London is regulated by the Office for Students.
The study time and assessment methods detailed above are typical and give you a good indication of what to expect. However, they are subject to change.
You are required to take:
MSc
PG Dip
PG Cert
Optional modules include
Seminars and workshops: MSc: Students must attend an introductory statistical programming workshop and attend one departmental seminar and one research seminar per term. Students must also attend the ASMHI Seminar Series throughout the year. PG Dip: Students must attend an introductory statistical programming workshop and attend one departmental seminar and one research seminar per term. Students must also attend the ASMHI Seminar Series throughout the year. PG Cert: Students must attend an introductory statistical programming workshop at the start of the year. Students may also choose to attend the ASMHI Seminar Series that takes place throughout the year.
King’s College London reviews the modules offered on a regular basis to provide up-to-date, innovative and relevant programmes of study. Therefore, modules offered may change. We suggest you keep an eye on the course finder on our website for updates.
Please note that modules with a practical component will be capped due to educational requirements, which may mean that we cannot guarantee a place to all students who elect to study this module.
There is an increasing demand for individuals who can understand and manage information and information systems as well as analyse and interpret complex data in industry, public health sector and academia.
This programme offers a unique blend of training in applied statistics and health informatics science to enable graduates for roles in this rapidly emerging field of data-intensive medical research. Upon completion, you will have a solid understanding of the methodologies and application that are relevant to design and implement clinical research studies that take advantage of the increasing availability of multimodal and big data. This will include health data acquisition, storage, interoperability, data analyses, and interpretation and communication of findings. Postgraduate qualifications are often required to progress to senior positions.
Our course will help you to develop your career in the medical research and health sector, including public health service (NHS), pharmaceutical and computer companies, technology start-ups, government agencies as well as academia, and other scientific organizations. Knowledge of applied statistical modelling and data science will also open careers in other sectors such as banking, marketing, insurance, and consulting. It will also provide a strong foundation for students interested in obtaining a PhD in biostatistics, data science, psychology, medicine, or informatics with an emphasis on applications in health science.
Full time: £16,950 per year (MSc, 2025/26); £11,300 per year (PG Dip, 2025/26); £5,650 per year (PG Cert, 2025/26);
Full time: £40,000 per year (MSc, 2025/26); £26,557 per year (PG Dip, 2025/26); £13,333 per year (PG Cert, 2025/26);
These tuition fees may be subject to additional increases in subsequent years of study, in line with King’s terms and conditions.
If you receive an offer for this programme, you will be required to pay a non-refundable deposit to secure your place. Deposit payments are credited towards the total tuition fee payment.
The Home deposit is £500. The International deposit is £2000.
If you are a current undergraduate King’s student in receipt of the King's Living Bursary this academic year, you are not required to pay a deposit to secure your place on the programme. Please note, this will not change the total fees payable for your chosen programme.
Please visit our web pages on fees and funding for more information.
Department of Biostatistics and Health Informatics Scholarship
Scholarship of £5000 are available for 2025/26 applicants. For more information click here.
In addition to your tuition costs, you can also expect to pay for:
To find out more about bursaries, scholarships, grants, tuition fees, living expenses, student loans, and other financial help available at King's please visit the Fees and Funding section.
Our course is to meet the growing need for a graduate training course that focuses on methodological skills to respond to problems of “big data” of complexes diseases, which is underpinned by strong statistical methodology and real-world application.” There is an increasing demand for the acquisition, storage, retrieval and use of information within private and public sector institutions engaged in health research. The range of modern medical data is vast, from patient records, genetics, other omics and imaging data to real-time measures of physiological responses from wearable sensors, smartphone social media use and environmental data. We will provide you with the necessary state-of-the-art statistical modelling and health informatics techniques to manage and evaluate this data. You will receive training in key methodological techniques underpinning “big data” acquisition, information retrieval and analysis using prediction modelling and theory-driven analyses approaches. You will benefit from the teaching of world-renowned experts in the field, you will conduct an applied research project and link to statistical and health informatics research groups, such as the Causal Analysis and Evaluation, Precision Medicine and Statistical Learning, Psychometrics and Measurement Lab, Structural Equation Modelling group, Precision Health Informatics Data Lab and Natural Language Processing groups in the Department of Biostatistics and Health Informatics. You will be part of a multi-professional cohort, bringing together diverse points of view on national and international modern data dilemmas. You will also have the unique opportunity to network and develop career opportunities. Our course combines training in core statistical modelling, health informatics and computational methodology, beginning at an introductory level, with a range of optional modules. The course uses a blended design to teaching and learning, where students access pre-recorded lectures from world’s leading experts, complemented by face to face workshops and seminars to ensure students have a rich and exciting learning experience from the start.
Home to the Institute of Psychiatry, Psychology & Neuroscience.
Please note that locations are determined by where each module is taught and may vary depending on the modules you study.
King's is regulated by the Office for Students
A minimum 2:1 undergraduate Bachelor’s (honours) degree
If you have a lower degree classification, or a degree in an unrelated subject, your application may be considered if you can demonstrate significant relevant work experience, or offer a related graduate qualification (such as a Masters or PGDip).
A bachelor’s degree with 2:1 honours in Computer Science, Mathematics, Statistics, Physics, Natural Sciences, Electronic Engineering, Psychology or Geographic Information Systems. In order to meet the academic entry requirements for this programme you should have a minimum 2:1 undergraduate degree, if you are still studying you should be achieving an average of at least 60% or above in the UK marking scheme.
Other degrees or professional qualifications may be acceptable, such as the Graduate diploma of the Royal Statistical Society.
To study at King's, it is essential that you can communicate in English effectively in an academic environment. You are usually required to provide certification of your competence in English before starting your studies.
Nationals of majority English speaking countries (as defined by the UKVI) who have permanently resided in this country are not usually required to complete an additional English language test. This is also the case for applicants who have successfully completed an undergraduate degree (of at least three years duration), a postgraduate taught degree (of at least one year), or a PhD in a majority English speaking country (as defined by the UKVI) within five years of the course start date.
For information on our English language requirements and whether you need to complete an English language test, please see our English Language requirements page.
Applications must be made online using King’s online application portal apply.kcl.ac.uk and a non-refundable application fee of £85 applies.
Selection is made on the basis of application and references. Potential students are welcome to visit the department: please arrange a suitable time in advance.
You will be asked to submit the following documents in order for your application to be considered:
| Personal Statement | Yes |
Q1. Why are you applying for this specific programme, and how does it fit in with your future plans? Q2. How does your educational background or professional experience make you a suitable candidate for the programme? Q3. Describe a project where you applied statistical or analytical methods, either in an academic or professional setting. What was your role, and which statistical packages, programming languages, or research techniques did you use in this project? If you have limited experience, describe any relevant coursework, self-directed learning, or projects demonstrating your interest and skills in these areas. |
|---|---|---|
| Previous Academic Study | Yes | A copy (or copies) of your official academic transcript(s), showing the subjects studied and marks obtained. If you have already completed your degree, copies of your official degree certificate will also be required. Applicants with academic documents issued in a language other than English, will need to submit both the original and official translation of their documents. |
| References | Yes | One academic reference is required. A professional reference will be accepted if you have completed your qualifications over five years ago. |
| Other | Optional | You may wish to include a CV (Resume) or evidence of professional registration as part of your application. |
Our course combines training in core statistical modelling, health informatics and computational methodology, beginning at an introductory level, with a range of optional modules.
The course uses a blended design to teaching and learning, where students access pre-recorded lectures from world’s leading experts, complemented by face to face workshops and seminars to ensure students have a rich and exciting learning experience from the start.
Each year you will take:
The course uses a blended design to teaching and learning, where students access pre-recorded lectures from world’s leading experts, complemented by face to face workshops and seminars to ensure students have a rich and exciting learning experience from the start.
Teaching
You will be taught through a mix of pre-recorded lectures, tutorials, seminars and digital activities.
| Module name | Lectures (hours) | Seminars/tutorials (hours) | Self-directed study (hours) | Total (hours) |
| Introduction to Statistical Modelling | 40 | 60 | 200 | 300 |
| Introduction to Health Informatics | 20 | 30 | 100 | 150 |
| Multilevel and Longitudinal Modelling | 20 | 30 | 100 | 150 |
| Prediction Modelling | 20 | 30 | 100 | 150 |
| Causal Modelling and Evaluation | 20 | 30 | 100 | 150 |
| Machine Learning for Health and Bioinformatics | 20 | 30 | 100 | 150 |
| Clinical trials: A practical approach | 20 | 30 | 100 | 150 |
| Natural Language Processing (NLP) | 20 | 30 | 100 | 150 |
| Latent Variable and Structural Equation Modelling | 20 | 30 | 100 | 150 |
| Artificial Intelligence for Healthcare Analytics | 20 | 30 | 100 |
150 |
| ASMHI Research Project | 0 | 60 | 540 |
600 |
Typically, one credit equates to 10 hours of work.
Location
Our course is primarily taught on campus at the King’s College London Denmark Hill Campus.
The primary methods of assessment for this course are written examinations, coursework and an e- portfolio of competencies and skills, to support your employability and development. The study time and assessment methods typically give an indication of what to expect. However, these may vary depending upon the modules.
For the full MSc each student will need to complete the ASMHI Research Project module, where assessment will be made up of a dissertation/research report and a poster/viva.
Regulating body
King’s College London is regulated by the Office for Students.
The study time and assessment methods detailed above are typical and give you a good indication of what to expect. However, they are subject to change.
You are required to take:
MSc
PG Dip
PG Cert
Optional modules include
Seminars and workshops: MSc: Students must attend an introductory statistical programming workshop and attend one departmental seminar and one research seminar per term. Students must also attend the ASMHI Seminar Series throughout the year. PG Dip: Students must attend an introductory statistical programming workshop and attend one departmental seminar and one research seminar per term. Students must also attend the ASMHI Seminar Series throughout the year. PG Cert: Students must attend an introductory statistical programming workshop at the start of the year. Students may also choose to attend the ASMHI Seminar Series that takes place throughout the year.
King’s College London reviews the modules offered on a regular basis to provide up-to-date, innovative and relevant programmes of study. Therefore, modules offered may change. We suggest you keep an eye on the course finder on our website for updates.
Please note that modules with a practical component will be capped due to educational requirements, which may mean that we cannot guarantee a place to all students who elect to study this module.
There is an increasing demand for individuals who can understand and manage information and information systems as well as analyse and interpret complex data in industry, public health sector and academia.
This programme offers a unique blend of training in applied statistics and health informatics science to enable graduates for roles in this rapidly emerging field of data-intensive medical research. Upon completion, you will have a solid understanding of the methodologies and application that are relevant to design and implement clinical research studies that take advantage of the increasing availability of multimodal and big data. This will include health data acquisition, storage, interoperability, data analyses, and interpretation and communication of findings. Postgraduate qualifications are often required to progress to senior positions.
Our course will help you to develop your career in the medical research and health sector, including public health service (NHS), pharmaceutical and computer companies, technology start-ups, government agencies as well as academia, and other scientific organizations. Knowledge of applied statistical modelling and data science will also open careers in other sectors such as banking, marketing, insurance, and consulting. It will also provide a strong foundation for students interested in obtaining a PhD in biostatistics, data science, psychology, medicine, or informatics with an emphasis on applications in health science.
Full time: £16,950 per year (MSc, 2025/26); £11,300 per year (PG Dip, 2025/26); £5,650 per year (PG Cert, 2025/26);
Full time: £40,000 per year (MSc, 2025/26); £26,557 per year (PG Dip, 2025/26); £13,333 per year (PG Cert, 2025/26);
These tuition fees may be subject to additional increases in subsequent years of study, in line with King’s terms and conditions.
If you receive an offer for this programme, you will be required to pay a non-refundable deposit to secure your place. Deposit payments are credited towards the total tuition fee payment.
The Home deposit is £500. The International deposit is £2000.
If you are a current undergraduate King’s student in receipt of the King's Living Bursary this academic year, you are not required to pay a deposit to secure your place on the programme. Please note, this will not change the total fees payable for your chosen programme.
Please visit our web pages on fees and funding for more information.
Department of Biostatistics and Health Informatics Scholarship
Scholarship of £5000 are available for 2025/26 applicants. For more information click here.
In addition to your tuition costs, you can also expect to pay for:
To find out more about bursaries, scholarships, grants, tuition fees, living expenses, student loans, and other financial help available at King's please visit the Fees and Funding section.
We encourage you to apply as early as possible so that there is sufficient time for your application to be assessed and we may need to request further information from you during the application process.
The final application deadlines for this programme are:
· Overseas (international) fee status: 25 July 2025 (23:59 UK time)
· Home fee status: 25 August 2025 (23:59 UK time)
If the programme becomes full before the final application deadlines stated above, we will close the programme to further applications. Please note, you will not be eligible for an application fee refund if we are unable to process further offers because places are filled and we close the course before the final application deadline.
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