The Genetics of Human Disease MSc aims to provide students with an in-depth knowledge of molecular genetics, quantitative and statistical genetics and human disease and how this can be applied to improve healthcare through the development and application of diagnostic tests and therapeutic agents.
The programme provides a thorough grounding in modern approaches to the understanding of the genetics of disease alongside the cutting-edge research methods and techniques used to advance our understanding of development of disease. Core modules provide a broad coverage of the genetics of disease, research skills and social aspects, whilst specialised streams in Inherited Diseases, Pharmacogenetics and Computational Genomics, in which students can qualify, and the research project allow more in-depth analysis in areas of genetics.
Students undertake modules to the value of 180 credits.
The programme consists of four core modules (60 credits) and two specialist modules (30 credits) and a research project culminating in a dissertation (90 credits).
A Postgraduate Diploma consisting of six modules (four core modules in term one and two modules within the selected stream in term two) is offered, full-time nine months.
A Postgraduate Certificate consisting of four core modules in term one (60 credits) is offered, full-time three months.
Core modules
Specialist modules
In term two you will take specialist modules depending on the specialist stream you select: Inherited Disease (A); Pharmacogenetics (B); Computational Genomics (C).
Dissertation/report
Students undertake an original research project investigating topical questions in genetics and genetics of human disease which culminates in a dissertation of 12,000 to 14,000 words and an oral presentation.
Teaching and learning
Students develop their knowledge and understanding of genetics of human diseases through a combination of lectures, seminars, tutorials, presentations and journal clubs. Taught modules are assessed by unseen written examination and/or, written reports, oral presentations and coursework. The research project is assessed by the dissertation and oral presentation.
Further information on modules and degree structure available on the UCL Genetics Institute website.
Further information on modules and degree structure is available on the department website: Genetics of Human Disease MSc
Advanced training in genetic techniques including bioinformatic and statistical approaches positions graduates well for PhD studentships in laboratories using genetic techniques to examine diseases such as heart disease, cancer and neurological disorders. Another large group will seek research jobs in the pharmaceutical industry, or jobs related to genetics in healthcare organisations.
Recent career destinations for this degree
Employability
The MSc in Genetics of Human Disease facilitates acquisition of knowledge and skills relevant to a career in research in many different biomedical disciplines. About half of our graduates enter a research career by undertaking and completing PhDs and working as research associates/scientists in academia. Some of our graduates go on to jobs in the pharmaceutical industry, while others enter careers with clinical genetic diagnosis services, particularly in molecular genetics, in healthcare organisations and hospitals around the world. Those graduates with a prior medical training often utilise their new skills as clinical geneticists.
Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.
UCL is in a unique position to offer both the basic science and application of modern genetics to improve human health. The programme is a cross-faculty initiative with teaching from across the School of Life and Medical Sciences (SLMS) at UCL.
Students will be based at the UCL Genetics Institute (UGI), a world-leading centre which develops and applies biostatistical and bioinformatic approaches to human and population genetics. Opportunities to conduct laboratory or computational-based research projects are available in the laboratories of world-leading geneticists affiliated to the UGI.
The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.
The following REF score was awarded to the department: Division of Biosciences
82% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)
Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.
This Masters in Biostatistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics; previous study of statistics is not required.
Modes of delivery of the Masters across the Statistics programmes include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.
Group 1
Group 2
1 Any student who, in the course of study for his or her first degree, has already completed the equivalent of the Probability and/or Statistical inference courses can substitute these courses by any other optional course (including optional courses offered as part of the MRes in Advanced Statistics). The choice of substituting courses is subject to approval by the Programme Director.
Summer (May – August)
Statistics project and dissertation (60) - applying statistical methods and modelling to data collected from research in a biomedical discipline, assessed by a dissertation.
Our graduates have an excellent track record of gaining employment in many sectors including medical research, the pharmaceutical industry, finance and government statistical services, while others have continued to a PhD.
This Masters in Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics.
Modes of delivery of the Masters across the Statistics programmes include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.
Group 1
Group 2
1 Any student who, in the course of study for his or her first degree, has already completed the equivalent of the Probability and/or Statistical inference courses can substitute these courses by any other optional course (including optional courses offered as part of the MRes in Advanced Statistics). The choice of substituting courses is subject to approval by the Programme Director.
Summer (May – August)
Statistics project and dissertation (60) - assessed by a dissertation.
Our graduates have an excellent track record of gaining employment in many sectors including finance, medical research, the pharmaceutical industry and government statistical services, while others have continued to a PhD.
This Masters in Advanced Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics.
Modes of delivery of the Masters across the Statistics programmes include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.
Summer (May – August)
Statistics project and dissertation (60) - assessed by a dissertation
Our graduates have an excellent track record of gaining employment in many sectors including medical research, the pharmaceutical industry, finance and government statistical services, while others have continued to a PhD.
The revolution in genetic mapping technology and the advent of whole genome sequences have turned quantitative genetics into one of the fastest growing areas of biology.
Based in the internationally renowned Institute of Evolutionary Biology, this MSc draws from the wealth of expertise available there, as well as the teaching, research expertise and facilities of Scotland’s Rural College, the University’s Centre for Molecular Medicine, the Medical Research Council’s Human Genetics Unit and the Roslin Institute (birthplace of Dolly the sheep).
Each year the syllabus is fine-tuned to suit current issues in evolutionary, plant, human and animal genetics.
This programme forms part of the quantitative genetics and genome analysis suite of programmes offering specialist routes, which also include Animal Breeding & Genetics and Human Complex Trait Genetics.
This programme consists of two semesters of taught courses followed by a research project, leading to a dissertation.
Courses are taught via lectures, tutorials, seminars and computer practicals. Assessment is by written examinations, in-course assignments and project work.
Compulsory courses:
Option courses:
You will gain the knowledge and skills required to apply quantitative genetics theory to undertake research in evolutionary and quantitative genetics, population genetics and evolutionary genomics.
You will develop the in-depth knowledge and specialised skills required to apply quantitative genetics theory to practical problems, in both the biomedical and animal science industries, and to undertake research in evolutionary genetics, population genetics and genome analysis.
The revolution in genetic mapping technology and the advent of whole genome sequences have turned quantitative genetics into one of the fastest growing areas of biology.
Based in the internationally renowned Institute of Evolutionary Biology, this MSc draws from the wealth of expertise available there, as well as the teaching, research expertise and facilities of Scotland’s Rural College, the University’s Centre for Molecular Medicine, the Medical Research Council’s Human Genetics Unit and the Roslin Institute (birthplace of Dolly the sheep).
Each year the syllabus is fine-tuned to suit current issues in evolutionary, plant, human and animal genetics.
This programme forms part of the quantitative genetics and genome analysis suite of programmes offering specialist routes, which include Animal Breeding & Genetics and Evolutionary Genetics.
This programme consists of two semesters of taught courses followed by a research project, leading to a dissertation.
Courses are taught via lectures, tutorials, seminars and computer practicals. Assessment is by written examinations, in-course assignments and project work.
Compulsory courses:
Option courses:
You will gain the knowledge and skills required to apply quantitative genetics theory to practical problems in the biomedical industry, and to undertake research in quantitative and population genetics and genome analysis.
You will develop the in-depth knowledge and specialised skills required to apply quantitative genetics theory to practical problems, in both the biomedical and animal science industries, and to undertake research in evolutionary genetics, population genetics and genome analysis.
The revolution in genetic mapping technology and the advent of whole genome sequences have turned quantitative genetics into one of the fastest growing areas of biology.
Based in the internationally renowned Institute of Evolutionary Biology, this MSc draws from the wealth of expertise available there, as well as the teaching, research expertise and facilities of Scotland’s Rural College, the University’s Centre for Genomics and Experimental Medicine, the Medical Research Council’s Human Genetics Unit and the Roslin Institute (birthplace of Dolly the sheep).
Each year the syllabus is fine-tuned to suit current issues in evolutionary, plant, human and animal genetics. This programme forms part of the quantitative genetics and genome analysis suite of programmes offering three specialist routes, which also include Human Complex Trait Genetics and Evolutionary Genetics.
This programme consists of two semesters of taught courses followed by a research project, leading to a dissertation.
Courses are taught via lectures, tutorials, seminars and computer practicals. Assessment is by written examinations, in-course assignments and project work.
Compulsory courses:
Option courses:
You will develop the in-depth knowledge and specialised skills required to apply quantitative genetics theory to practical problems, in both the biomedical and animal science industries, and to undertake research in evolutionary genetics, population genetics and genome analysis.
This Masters in Environmental Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics; previous study of statistics is not required.
Modes of delivery of the Masters across the Statistics programmes include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.
1 Any student who, in the course of study for his or her first degree, has already completed the equivalent of the Probability and/or Statistical inference courses can substitute these courses by any other optional course (including optional courses offered as part of the MRes in Advanced Statistics). The choice of substituting course is subject to approval by the Programme Director.
Summer (May – August)
Statistics project and dissertation (60) - applying statistical methods and modelling to data collected from research in environmental science, assessed by a dissertation.
Our graduates have an excellent track record of gaining employment in many sectors including medical research, the pharmaceutical industry, finance and government statistical services, while others have continued to a PhD.
Graduates of this programme have gone on to positions such as:
Research Officer Medical Statistics at Kenya Medical Research Institute (KEMRI) Welcome Trust.
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New Master's Scholarships available. Find out more and apply.
Our Genes, Environment & Development in Psychology & Psychiatry MSc course provides interdisciplinary training in a range of behavioural genetics topics and research methods relevant to psychology and psychiatry. You will study three required modules and undertake a research project on one of the broad range of subject areas that are considered fundamental to an understanding of behavioural genetics.
The MSc Genes, Environment & Development in Psychology and Psychiatry (GED PP) programme takes a highly interdisciplinary approach to the study of how genetics and the environment ('nature and nurture') combine during human development to produce behaviour, diseases and psychiatric disorders. Students are taught by world leading experts and receive training across multiple research fields: molecular & behavioural genetics, twin modelling, statistical genetics, epigenetics, bioinformatics, social and cognitive psychology and developmental psychiatry. Topics are taught from an introductory to advance level through both theoretical and hands-on practical sessions (wet and computer labs), followed by a supervised research project in an area of the student's interest. Students come from a range of academic backgrounds (e.g. genetics, psychology, maths, computing, medicine) and on completion of the course will be exceptionally well equipped to pursue a PhD or work for a pharmaceutical or healthcare organisation. More than half of the students secure PhD studentships while completing the MSc
In addition to disorder characterisation and presentation of the genetic, social and otherenvironmental risk factors, our course also covers the molecular mechanisms and the specialised analysis methods relevant to interdisciplinary research in this field. By focusing on current research in this area, our course will enhance your understanding of research methods and enable you to critically appraise the relevant scientific literature.
You will be taught through a mix of lectures, seminars and tutorials.
Year 1
You will be assessed through a combination of coursework and examinations.
Examination (15%) | Coursework (70%) | Practical (15%)
Regulating body
King’s College is regulated by the Higher Education Funding Council for England
Our graduates go on to further full-time study in an academic research environment or in a taught clinical programme, gain employment in an academic, clinical or pharmaceutical organisation. Some students may enter scientific publishing.
An MSc is generally accepted as being highly desirable for starting and developing a career in Medical Statistics. The MSc in Statistics with Applications in Medicine is also an excellent preparation for embarking on a PhD project in Statistics or Medical Statistics.
The MSc in Statistics with Applications in Medicine, taught by one of the largest and strongest Statistics groups in the UK, will provide you with a sound Masters-level training in Statistical methodology, with an emphasis on practical problems arising in the context of collecting and analysing Medical data. Several modules are delivered by Medical Statisticians, who can provide data and case studies from their own day to day work at Southampton General Hospital and the Medical Research Council Lifecourse Epidemiology Unit.
While studying for your degree, you will develop key transferrable skills, such as written and oral communication, the use of and some programming in Statistical software, time management, and basic research skills.
Programme objectives are:
Careers:
Past graduates have joined major pharmaceutical companies, research teams at the Medical Research Council, university-based medical research units, contract research organisations, government, the financial sector, or have continued with further study to become successful PhD students.
The ever-increasing amount and range of patient data presents the pharmaceutical industry and medical research institutions with significant challenges and great opportunities. Medical Statisticians design and analyse clinical trials for new treatments; they help to identify the genes responsible for disease and they developing methodology to enable advances in personalised medicine.
Their work underpins scientific breakthroughs that will be life-saving for many. In the MSc in Statistics with Applications in Medicine you will examine new developments in challenging medical data problems through the study of clinical trials, statistical genetics and epidemiological methods.
The full-time MSc is completed over a 12-month period. There are two semesters of taught material, which account for 60 ECTS credits, followed by the MSc project in summer, which accounts for 30 ECTS credits.
The programme structure allows you to select options ranging from the more theoretical aspects of Statistics, including a module on research topics, to those which cover material focussed on practical applications of Statistics in a clinical setting. This is complemented by modules on research skills, a Medical Statistics seminar series providing insight into the role of Medical Statisticians in various different careers (which also gives opportunities for networking with the speakers), and several presentations on transferrable skills by the University Careers and Employability Service Team.
View the programme specification document for this course
Data is becoming an ever increasing part of modern life, yet the talent to extract information and value from complex data is scarce. This Masters will provide you with a thorough grounding in state-of-the art methods for learning from data, both in terms of statistical modelling and computation. You will also gain practical hands-on experience in carrying out various data-driven analytical projects. Previous study of Statistics or Computing Science is not required.
One Course is optional for students with sufficient background in Linear Algebra and Calculus.
Two students who have already completed an equivalent course can substitute this course by any other optional course, including optional courses offered as part of the MRes in Advanced Statistics (see the website for details).
In your project (60 credits) you will model data collected from research in environmental science, assessed by a dissertation.
Students choose at least two courses from group 1 and at least one course from group 2.
Group 1
Group 2
Group 3
In your project (60 credits) you will tackle a complex data analytical problem or develop novel approaches to solving data analytical challenges.
There is a massive shortage of data-analytical skills in the workforce. Statistician is projected to be one of the fastest-growing occupations. There is a massive shortage of data-analytical skills in the workforce. Statistician is projected to be one of the fastest-growing occupations. Statistical Analysis and Data Mining was listed by LinkedIn as the hottest skill in 2014 and came second in 2015.
Our graduates have an excellent track record of gaining employment in many sectors including medical research, the pharmaceutical industry, finance and government statistical services, while others have continued to a PhD. Our recent graduates have taken up positions as Statisticians with the Scottish Government, as Advanced Analytics Analyst at Deloitte Ireland, as Consultant at the World Bank and as Research Officer at Kenya Medical Research Institute (KEMRI).
Life Sciences is one of the strategic research fields at the University of Helsinki. The multidisciplinary Master’s Programme in Life Science Informatics (LSI) integrates research excellence and research infrastructures in the Helsinki Institute of Life Sciences (HiLIFE).
The Master's Programme is offered by the Faculty of Science. Teaching is offered in co-operation with the Faculty of Medicine and the Faculty of Biological and Environmental Sciences. As a student, you will gain access to active research communities on three campuses: Kumpula, Viikki, and Meilahti. The unique combination of study opportunities tailored from the offering of the three campuses provides an attractive educational profile. The LSI programme is designed for students with a background in mathematics, computer science and statistics, as well as for students with these disciplines as a minor in their bachelor’s degree, with their major being, for example, ecology, evolutionary biology or genetics. As a graduate of the LSI programme you will:
Further information about the studies on the Master's programme website.
The Life Science Informatics Master’s Programme has six specialisation areas, each anchored in its own research group or groups.
Algorithmic bioinformatics with the Genome-scale algorithmics, Combinatorial Pattern Matching, and Practical Algorithms and Data Structures on Strings research groups. This specialisation area educates you to be an algorithm expert who can turn biological questions into appropriate challenges for computational data analysis. In addition to the tailored algorithm studies for analysing molecular biology measurement data, the curriculum includes general algorithm and machine learning studies offered by the Master's Programmes in Computer Science and Data Science.
Applied bioinformatics, jointly with The Institute of Biotechnology and genetics.Bioinformatics has become an integral part of biological research, where innovative computational approaches are often required to achieve high-impact findings in an increasingly data-dense environment. Studies in applied bioinformatics prepare you for a post as a bioinformatics expert in a genomics research lab, working with processing, analysing and interpreting Next-Generation Sequencing (NGS) data, and working with integrated analysis of genomic and other biological data, and population genetics.
Biomathematics with the Biomathematics research group, focusing on mathematical modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of topics ranging from problems at the molecular level to the structure of populations. To tackle these problems, the research group uses a variety of modelling approaches, most importantly ordinary and partial differential equations, integral equations and stochastic processes. A successful analysis of the models requires the study of pure research in, for instance, the theory of infinite dimensional dynamical systems; such research is also carried out by the group.
Biostatistics and bioinformatics is offered jointly by the statistics curriculum, the Master´s Programme in Mathematics and Statistics and the research groups Statistical and Translational Genetics, Computational Genomics and Computational Systems Medicine in FIMM. Topics and themes include statistical, especially Bayesian methodologies for the life sciences, with research focusing on modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of collaborative topics in various biomedical disciplines. In particular, research and teaching address questions of population genetics, phylogenetic inference, genome-wide association studies and epidemiology of complex diseases.
Eco-evolutionary Informatics with ecology and evolutionary biology, in which several researchers and teachers have a background in mathematics, statistics and computer science. Ecology studies the distribution and abundance of species, and their interactions with other species and the environment. Evolutionary biology studies processes supporting biodiversity on different levels from genes to populations and ecosystems. These sciences have a key role in responding to global environmental challenges. Mathematical and statistical modelling, computer science and bioinformatics have an important role in research and teaching.
Systems biology and medicine with the Genome-scale Biology Research Program in Biomedicum. The focus is to understand and find effective means to overcome drug resistance in cancers. The approach is to use systems biology, i.e., integration of large and complex molecular and clinical data (big data) from cancer patients with computational methods and wet lab experiments, to identify efficient patient-specific therapeutic targets. Particular interest is focused on developing and applying machine learning based methods that enable integration of various types of molecular data (DNA, RNA, proteomics, etc.) to clinical information.
