Masters Degrees (Statistical Genetics)

Programme description

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.

Programme structure

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:

• Population and Quantitative Genetics
• Genetic Interpretation
• Linkage and Association in Genome Analysis
• Statistics and Data Analysis
• Research Proposal
• Dissertation

Option courses:

• Molecular Phylogenetics
• Bioinformatics
• Molecular Evolution
• Genetics of Human Complex Traits
• Quantitative Genetic Models
• Functional Genomic Technologies
• Animal Genetic Improvement
• Evolutionary Quantitative Genetics

Learning outcomes

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.

• A thorough understanding of general concepts in population and quantitative genetics and genomics
• In-depth knowledge of evolutionary genetics
• A solid grounding in the statistical methods required for quantitative biology
• Development of independent research skills through individual mini- and maxi-research projects
• Development of generic skills (IT skills, experience in writing scientific papers, the ability to work independently)
• Presentation skills through student seminars, scientific presentation of project work and independent research projects.

Career opportunities

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.

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The Institute of Genetic Medicine brings together a strong team with an interest in clinical and developmental genetics. Our research focuses on the causes of genetic disease at the molecular and cellular level and its treatment. Research areas include: genetic medicine, developmental genetics, neuromuscular and neurological genetics, mitochondrial genetics and cardiovascular genetics.

As a research postgraduate in the Institute of Genetic Medicine you will be a member of our thriving research community. The Institute is located in Newcastle’s Life Science Centre. You will work alongside a number of research, clinical and educational organisations, including the Northern Genetics Service.

We offer supervision for MPhil in the following research areas:

Cancer genetics and genome instability

Our research includes:
-A major clinical trial for chemoprevention of colon cancer
-Genetic analyses of neuroblastoma susceptibility
-Research into Wilms Tumour (a childhood kidney cancer)
-Studies on cell cycle regulation and genome instability

Cardiovascular genetics and development

We use techniques of high-throughput genetic analyses to identify mechanisms where genetic variability between individuals contributes to the risk of developing cardiovascular disease. We also use mouse, zebrafish and stem cell models to understand the ways in which particular gene families' genetic and environmental factors are involved in the normal and abnormal development of the heart and blood vessels.

Complex disease and quantitative genetics

We work on large-scale studies into the genetic basis of common diseases with complex genetic causes, for example autoimmune disease, complex cardiovascular traits and renal disorders. We are also developing novel statistical methods and tools for analysing this genetic data.

Developmental genetics

We study genes known (or suspected to be) involved in malformations found in newborn babies. These include genes involved in normal and abnormal development of the face, brain, heart, muscle and kidney system. Our research includes the use of knockout mice and zebrafish as laboratory models.

Gene expression and regulation in normal development and disease

We research how gene expression is controlled during development and misregulated in diseases, including the roles of transcription factors, RNA binding proteins and the signalling pathways that control these. We conduct studies of early human brain development, including gene expression analysis, primary cell culture models, and 3D visualisation and modelling.

Genetics of neurological disorders

Our research includes:
-The identification of genes that in isolation can cause neurological disorders
-Molecular mechanisms and treatment of neurometabolic disease
-Complex genetics of common neurological disorders including Parkinson's disease and Alzheimer's disease
-The genetics of epilepsy

Kidney genetics and development

Kidney research focuses on:
-Atypical haemolytic uraemic syndrome (aHUS)
-Vesicoureteric reflux (VUR)
-Cystic renal disease
-Nephrolithiasis to study renal genetics

The discovery that aHUS is a disease of complement dysregulation has led to a specific interest in complement genetics.

Mitochondrial disease

Our research includes:
-Investigation of the role of mitochondria in human disease
-Nuclear-mitochondrial interactions in disease
-The inheritance of mitochondrial DNA heteroplasmy
-Mitochondrial function in stem cells

Neuromuscular genetics

The Neuromuscular Research Group has a series of basic research programmes looking at the function of novel muscle proteins and their roles in pathogenesis. Recently developed translational research programmes are seeking therapeutic targets for various muscle diseases.

Stem cell biology

We research human embryonic stem (ES) cells, germline stem cells and somatic stem cells. ES cell research is aimed at understanding stem cell pluripotency, self-renewal, survival and epigenetic control of differentiation and development. This includes the functional analysis of genes involved in germline stem cell proliferation and differentiation. Somatic stem cell projects include programmes on umbilical cord blood stem cells, haematopoietic progenitors, and limbal stem cells.

Pharmacy

Our new School of Pharmacy has scientists and clinicians working together on all aspects of pharmaceutical sciences and clinical pharmacy.

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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.

Programme structure

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:

• Population and Quantitative Genetics
• Genetic Interpretation
• Linkage and Association in Genome Analysis
• Genetics of Human Complex Traits
• Quantitative Genetic Models
• Statistics and Data Analysis
• Research Project Proposal
• Dissertation.

Option courses:

• Molecular Phylogenetics
• Bioinformatics
• Molecular Evolution
• Quantitative Genetic Models
• Functional Genomic Technologies
• Animal Genetic Improvement
• Evolutionary Quantitative Genetics

Learning outcomes

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.

• A thorough understanding of general concepts in population and quantitative genetics and genomics
• In-depth knowledge of complex trait genetics in humans
• A solid grounding in the statistical methods required for quantitative biology
• Development of independent research skills through individual mini- and maxi-research projects
• Development of generic skills (IT skills, experience in writing scientific papers, the ability to work independently)
• Presentation skills through student seminars, scientific presentation of project work and independent research projects.

Career opportunities

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.

Read less

Programme description

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.

Programme structure

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:

• Population and Quantitative Genetics
• Genetic Interpretation
• Statistics and Data Analysis
• Linkage and Association in Genome Analysis
• Animal Genetic Improvement
• Quantitative Genetic Models
• Research Proposal
• Dissertation

Option courses:

• Molecular Phylogenetics
• Bioinformatics
• Molecular Evolution
• Genetics of Human Complex Traits
• Functional Genomic Technologies
• Evolutionary Quantitative Genetics

Learning outcomes

• An understanding of general concepts in population and quantitative genetics and genomics
• A solid grounding in the statistical methods required
• In-depth knowledge of animal improvement and complex trait analysis
• Development of independent research skills through individual mini- and maxi-research projects
• Development of generic skills (IT skills, experience in writing scientific papers, the ability to work independently)
• Presentation skills through student seminars, scientific presentation of project work and independent research projects.

Career opportunities

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.

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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.

Why this programme

◾The Statistics Group at Glasgow is a large group, internationally renowned for its research excellence.
◾Our Statistics MSc programmes benefit from close links lecturers have with industry and non-governmental organisations such as NHS and SEPA.
◾Our expertise spans topics including: biostatistics and statistical genetics; environmental statistics; statistical methodology; statistical modelling and the scholarship of learning and teaching in statistics.
◾You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.
◾You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.

Programme structure

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..

Core courses (compulsory)
◾Bayesian statistics
◾Biostatistics
◾Generalised linear models
◾Introduction to R programming
◾Probability 1
◾Regression models
◾Statistical inference 1
◾Statistics project and dissertation.

Optional courses (five chosen, but at least one course must be from Group 1)
Group 1
◾Data analysis
◾Professional skills.

Group 2
◾Data management and analytics using SAS
◾Design of experiments
◾Functional data analysis
◾Spatial statistics
◾Statistical genetics
◾Time series.

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.

Career prospects

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.

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This programme qualifies for the prestigious Data Lab Masters Scholarships. The award covers full tuition fee costs. For further information please see: Data Lab Masters Scholarships.

Why this programme

◾The Statistics Group at Glasgow is a large group, internationally renowned for its research excellence.
◾Our expertise spans topics including: biostatistics and statistical genetics; environmental statistics; statistical methodology; statistical modelling and the scholarship of learning and teaching in statistics.
◾Our Statistics MSc programmes benefit from close links lecturers have with industry and non-governmental organisations such as NHS and SEPA.
◾You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.
◾You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.
◾You will be taught by world-leading experts in their fields and will participate in an extensive and varied seminar programme, are taught by internationally renowned lecturers and experience a wide variety of projects.
◾Our students graduate with a varied skill set, including core professional skills, and a portfolio of substantive applied and practical work.

Programme structure

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.

Courses include (twelve chosen)
◾Advanced Bayesian methods
◾Advanced data analysis
◾Bayesian statistics
◾Biostatistics
◾Computational inference
◾Data analysis
◾Data management and analytics using SAS
◾Design of experiments
◾Environmental statistics
◾Flexible regression
◾Financial statistics
◾Functional data analysis
◾Generalised linear models
◾Introduction to R programming
◾Linear mixed models
◾Machine learning
◾Multivariate methods
◾Principles of probability and statistics
◾Professional skills
◾Spatial statistics
◾Statistical genetics
◾Stochastic processes
◾Time series
◾Statistics project and dissertation.

Summer (May – August)
Statistics project and dissertation (60) - assessed by a dissertation

Career prospects

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.

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This Masters in Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics.

Why this programme

◾The Statistics Group at Glasgow is a large group, internationally renowned for its research excellence.
◾Our expertise spans topics including: biostatistics and statistical genetics; environmental statistics; statistical methodology; statistical modelling and the scholarship of learning and teaching in statistics.
◾Our Statistics MSc programmes benefit from close links lecturers have with industry and non-governmental organisations such as NHS and SEPA.
◾You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.
◾You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.
◾You will be taught by world-leading experts in their fields and will participate in an extensive and varied seminar programme, are taught by internationally renowned lecturers and experience a wide variety of projects.
◾Our students graduate with a varied skill set, including core professional skills, and a portfolio of substantive applied and practical work.

Programme structure

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.

Core courses (compulsory)
◾Bayesian statistics
◾Generalised linear models
◾Introduction to R programming
◾Probability 1
◾Regression models
◾Statistical inference 1
◾Statistics project and dissertation.

Optional courses (six chosen, but at least one course must be from Group 1)

Group 1
◾Data analysis
◾Professional skills.

Group 2
◾Biostatistics
◾Computational inference
◾Data management and analytics using SAS
◾Design of experiments
◾Environmental statistics
◾Financial statistics
◾Functional data analysis
◾Machine learning
◾Multivariate methods
◾Spatial statistics
◾Statistical genetics
◾Stochastic processes
◾Time series.

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.

Career prospects

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.

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Summary

This course provides a broad grounding in advanced statistical methods, with a focus on applications in research, the NHS and the pharmaceutical industry; the course structure also allows mathematicians with some statistical experience to move into this field.

Modules

Analysis of repeated measures; bayesian methods; biological assay; clinical trials; communications and research skills; computer-intensive statistical methods; design and analysis of experiments; epidemiological studies; generalised linear models; multi-level modelling; multivariate distribution theory and inference; statistical computing; statistical genetics; survival analysis; univariate theory and inference; dissertation.

Visit our website for further information...

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This MSc has a strong theoretical and methodological component to supplement a focus on applications of statistics to real life scientific problems. You can opt to follow pathways in medical, pharmaceutical or environmental statistics, depending on your field of interest. Graduates tend to enter careers as practising statisticians, university research assistants or go on to study for a PhD.

For each pathway, you will follow a set of compulsory modules covering core theory and methods, applied statistical modelling and practical skills in topics such as statistical computing, scientific writing, presentation and consultancy. You will also study optional modules tailored to your research interests and career aspirations. Your studies are completed with a supervised, in-depth, dissertation aimed at solving a substantive research question.

Modules
Compulsory modules:
• Statistics in Practice
• Likelihood Inference
• Generalised Linear Models
• Bayesian Inference
• Computational Intensive Methods

Optional modules (choose five from):
• Extreme Value Theory
• Clinical Trials
• Principles of Epidemiology
• Statistical Genetics and Genomics
• Longitudinal Data Analysis
• Pharmacological Modelling
• Survival and Event History Analysis
• Adaptive/Bayesian Methods in Clinical Research
• Environmental Epidemiology

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The MSc in Statistics is a flexible degree programme enabling students from a wide range of backgrounds to both broaden and deepen their understanding of statistics.

The programme combines in-depth training in mainstream advanced statistical modelling with a broad range of specialisations - from financial mathematics to statistical bioinformatics; from shape analysis to risk management. You’ll also develop your understanding of research methods in statistics from writing styles to programming skills, preparing you for a wide range of careers in different sectors – and then apply them to a substantial research project of your own.

If you do not meet the full academic entry requirements then you may wish to consider the Graduate Diploma in Mathematics. This course is aimed at students who would like to study for a mathematics related MSc course but do not currently meet the entry requirements. Upon completion of the Graduate Diploma, students who meet the required performance level will be eligible for entry onto a number of related MSc courses, in the following academic year.

Accreditation

Royal statistical Society Accreditation

On graduation you will be eligible for the Graduate Statistician (GradStat) status and after five years’ experience this can be converted into the professional status of Chartered Statistician (CStat).

Being a chartered statistician provides employers, contractors and collaborators of statisticians a level of assurance that you are at the forefront of your field and is a mark of accomplishment to society.

Course content

The first two semesters of your course will consist of taught modules and in the third semester you will devote your time to a major dissertation.

Within each semester there is one compulsory module and a range of optional modules, allowing you to specialise in the area of statistics of most interest to you. Specialist areas within the course include biological or financial applications of statistics or broad based statistical expertise.The core modules will develop your skills to lay the groundwork of the programme. You’ll learn a range of statistical computing techniques and build research skills such as academic writing, programming and literature searches. Options within the course vary from mainstream topics in statistical methodology to more specialised areas and reflect specific research interests of our academic staff - examples include statistical shape analysis, directional data, statistical genetics and stochastic financial modelling.

Course structure

Compulsory modules

• Independent Learning and Skills Project 15 credits
• Statistical Computing 15 credits
• Dissertation in Statistics 60 credits

Optional modules

• Introduction to Clinical Trials 15 credits
• Core Epidemiology 15 credits
• Multilevel and Latent variable Modelling 15 credits
• Advanced Modelling Strategies 15 credits
• Advanced epidemiological techniques 15 credits
• Mathematical Biology 15 credits
• Linear Regression and Robustness 15 credits
• Statistical Theory 15 credits
• Stochastic Financial Modelling 15 credits
• Multivariate Analysis 10 credits
• Time Series 10 credits
• Bayesian Statistics 10 credits
• Generalised Linear Models 10 credits
• Introduction to Statistics and DNA 10 credits
• Discrete Time Finance 15 credits
• Continuous Time Finance 15 credits
• Risk Management 15 credits
• Advanced Mathematical Biology 20 credits
• Linear Regression and Robustness and Smoothing 20 credits
• Multivariate and Cluster Analysis 15 credits
• Time Series and Spectral Analysis 15 credits
• Bayesian Statistics and Causality 15 credits
• Generalised Linear and Additive Models 15 credits
• Statistics and DNA 15 credits

For more information on typical modules, read Statistics MSc in the course catalogue

Learning and teaching

Teaching is by lectures, tutorials, seminars and supervised research projects.

Assessment

The taught course is primarily assessed by end-of-semester examinations with a small component of continuous assessment. The semester three project is assessed by a written dissertation and a short oral presentation.

Career opportunities

There is a shortage of well-qualified statisticians in the UK and other countries. Numeracy, in general, is an attribute keenly sought after by employers.

The emergence of data mining and analysis means that demand for statisticians is growing across a wide range of professions - actuarial, betting and gaming industries, charitable organisations, commercial, environmental, financial, forensic and police investigation, government, market research, medical and pharmaceutical organisations. The course is designed specifically to meet this demand.

Many statistical careers require people educated to masters degree level. This course is designed to build on existing mathematical skills and deepen knowledge of statistics in order for you to access a variety of professions or pursue further research as a PhD student.

Careers support

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.

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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.

Degree Information

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
- Advanced Human Genetics: Research Principles
- Human Genetics in Context
- Core Skills
- Basic Statistics for Medical Sciences

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).
- Applications in Human Genetics (A)
- Either Genetics of Cardiovascular Disease or Genetics of Neurological Disease (A)
- Clinical Applications of Pharmacogenetic Tests (B)
- Anti-Cancer Personalised Medicine or Pharmacogenomics, Adverse Drug Reactions and Biomarkers (B)
- Applications in Human Genetics (C)
- Statistics for Interpreting Genetic Data (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.

Careers

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.

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.

Why study this degree at UCL?

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.

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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.

Why this programme

◾The Statistics Group at Glasgow is a large group, internationally renowned for its research excellence.
◾Our Statistics MSc programmes benefit from close links lecturers have with industry and non-governmental organisations such as NHS and SEPA.
◾Our expertise spans topics including: biostatistics and statistical genetics; environmental statistics; statistical methodology; statistical modelling and the scholarship of learning and teaching in statistics.
◾You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.
◾You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.
◾You will be taught by world-leading experts in their fields and will participate in an extensive and varied seminar programme, are taught by internationally renowned lecturers and experience a wide variety of projects.
◾Our students graduate with a varied skill set, including core professional skills, and a portfolio of substantive applied and practical work.

Programme structure

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.

Core courses (compulsory)
◾Bayesian statistics
◾Data analysis
◾Environmental statistics
◾Generalised linear models
◾Introduction to R programming
◾Principles of GIS (10)
◾Probability 1
◾Regression models
◾Spatial statistics
◾Statistical inference 1
◾Time series
◾Topographic mapping and landscape monitoring
◾Statistics project and dissertation.

Career prospects

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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International Master's in Statistics - MSc: https://www.kent.ac.uk/courses/postgraduate/163/international-masters-statistics

Overview

The International Master’s in Statistics develops your practical, statistical and computing skills to prepare you for a professional career in statistics or as a solid basis for further research in the area.

The programme has been designed to provide a deep understanding of the modern statistical methods required to model and analyse data. You will benefit from a thorough grounding in the ideas underlying these methods and develop your skills in key areas such as practical data analysis and data modelling.

It has been accredited by the Royal Statistical Society (RSS) and equips aspiring professional statisticians with the skills they need for posts in industry, government, research and teaching. It also enables you to develop a range of transferable skills that are attractive to employers within the public and private sectors.

Students whose mathematical and statistical background is insufficient for direct entry on to the appropriate programme, may apply for this course. The first year of the programme gives you a strong background in statistics, including its mathematical aspects, equivalent to the Graduate Diploma in Statistics. This is followed by the MSc in Statistics.

International Master's in Statistics with Finance - MSc: https://www.kent.ac.uk/courses/postgraduate/164/international-masters-statistics-finance

Overview

This programme, accredited by the Royal Statistical Society (RSS), equips aspiring professional statisticians with the skills they will need for posts in industry, government, research and teaching. It is suitable preparation too for careers in other fields requiring a strong statistical background.

Students whose mathematical and statistical background is insufficient for direct entry on to the appropriate programme, may apply for this course. The first year of the programme gives you a strong background in statistics, including its mathematical aspects, equivalent to the Graduate Diploma in Statistics. This is followed by the MSc in Statistics with Finance.

About the School of Mathematics, Statistics and Actuarial Science (SMSAS)

The School has a strong reputation for world-class research and a well-established system of support and training, with a high level of contact between staff and research students. Postgraduate students develop analytical, communication and research skills. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School. We encourage all postgraduate statistics students to take part in statistics seminars and to help in tutorial classes.

The Statistics Group is forward-thinking, with varied research, and received consistently high rankings in the last two Research Assessment Exercises.

Statistics at Kent provides:

- a programme that gives you the opportunity to develop practical, mathematical and computing skills in statistics, while working on challenging and important problems relevant to a broad range of potential employers

- teaching and supervision by staff who are research-active, with established reputations and who are accessible, supportive and genuinely interested in your work

- advanced and accessible computing and other facilities

- a congenial work atmosphere with pleasant surroundings, where you can socialise and discuss issues with a community of other students.

Research areas

Biometry and ecological statistics
Specific interests are in biometry, cluster analysis, stochastic population processes, analysis of discrete data, analysis of quantal assay data, overdispersion, and we enjoy good links within the University, including the School of Biosciences and the Durrell Institute of Conservation and Ecology. A recent major joint research project involves modelling the behaviour of yeast prions and builds upon previous work in this area. We also work in collaboration with many external institutions.

Bayesian statistics
Current work includes non-parametric Bayes, inference robustness, modelling with non-normal distributions, model uncertainty, variable selection and functional data analysis.
Bioinformatics, statistical genetics and medical statistics
Research covers bioinformatics (eg DNA microarray data), involving collaboration with the School of Biosciences. Other interests include population genetics, clinical trials and survival analysis.

Nonparametric statistics
Research focuses on empirical likelihood, high-dimensional data analysis, nonlinear dynamic analysis, semi-parametric modelling, survival analysis, risk insurance, functional data analysis, spatial data analysis, longitudinal data analysis, feature selection and wavelets.

Careers

Students often go into careers as professional statisticians in industry, government, research and teaching but our programmes also prepare you for careers in other fields requiring a strong statistical background. You have the opportunity to attend careers talks from professional statisticians working in industry and to attend networking meetings with employers.

Recent graduates have started careers in diverse areas such as the pharmaceutical industry, financial services and sports betting.

Professional recognition

The taught programmes in Statistics and Statistics with Finance provide exemption from the professional examinations of the Royal Statistical Society and qualification for Graduate Statistician status.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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This interdisciplinary MSc is aimed at students who wish to develop skills in the emerging discipline of Data Science. Building upon data science fundamentals, a variety of pathways through the MSc are available and allow students to choose from a range of elective modules according to their skills, interests and career aspirations. Students then undertake a 12-week summer placement either within industry (in a business setting), or as part of an academic research project to consolidate their learning.

Optional pathways span fundamentals and also application areas including:
• Business Analytics: how to gain business insight from large and complex industrial data
• Data Mining: how data mining can be performed at scale, and in a range of application areas (eg marketing and finance, social computing)
• Health Informatics: how to build models and gain insight to improve public health and aid clinical decision making
• Systems and Technologies: how to build large-scale systems for answering data science questions
• Statistical Inference: how to specify models and build a statistical framework to gain insights from data

Modules
Core modules:
• Data Mining
• Data Science Fundamentals
• Generalised Linear Models
• Likelihood Inference
• Programming for Data Scientists

Optional (elective) Modules:
• Applied Data Mining
• Clinical Trials
• Data Mining for Marketing, Sales and Finance
• Elements of Distributed Systems
• Environmental Epidemiology
• Extreme Value Theory
• Forecasting
• Longitudinal Data Analysis
• Methods for Missing Data
• Multi-level Modelling
• Optimisation and Heuristics
• Principles of Epidemiology
• Statistical Genetics and Genomics
• Survival Analysis
• Systems Architecture and Integration

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These programmes offers the opportunity to begin or consolidate your research career under the guidance of internationally renowned researchers and professionals in the School of Mathematics, Statistics and Actuarial Science (SMSAS).

Research interests are diverse and include: Bayesian statistics; bioinformatics; biometry; ecological statistics; epidemic modelling; medical statistics; nonparametric statistics and semi-parametric modelling; risk and queueing theory; shape statistics.

Visit the website https://www.kent.ac.uk/courses/postgraduate/169/statistics

About the School of Mathematics, Statistics and Actuarial Science (SMSAS):

The School has a strong reputation for world-class research and a well-established system of support and training, with a high level of contact between staff and research students. Postgraduate students develop analytical, communication and research skills. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School. We encourage all postgraduate statistics students to take part in statistics seminars and to help in tutorial classes.

The Statistics Group is forward-thinking, with varied research, and received consistently high rankings in the last two Research Assessment Exercises.

Statistics at Kent provides:

- a programme that gives you the opportunity to develop practical, mathematical and computing skills in statistics, while working on challenging and important problems relevant to a broad range of potential employers

- teaching and supervision by staff who are research-active, with established reputations and who are accessible, supportive and genuinely interested in your work

- advanced and accessible computing and other facilities

- a congenial work atmosphere with pleasant surroundings, where you can socialise and discuss issues with a community of other students.

Course structure

The research interests of the group are in line with the mainstream of statistics, with emphasis on both theoretical and applied subjects.

There are strong connections with a number of prestigious research universities such as Texas A&M University, the University of Texas, the University of Otago, the University of Sydney and other research institutions at home and abroad.

The group regularly receives research grants. The EPSRC has awarded two major grants, which support the National Centre for Statistical Ecology (NCSE), a joint venture between several institutions. A BBSRC grant supports stochastic modelling in bioscience.

Research areas

- Biometry and ecological statistics

Specific interests are in biometry, cluster analysis, stochastic population processes, analysis of discrete data, analysis of quantal assay data, overdispersion, and we enjoy good links within the University, including the School of Biosciences and the Durrell Institute of Conservation and Ecology. A recent major joint research project involves modelling the behaviour of yeast prions and builds upon previous work in this area. We also work in collaboration with many external institutions.

- Bayesian statistics

Current work includes non-parametric Bayes, inference robustness, modelling with non-normal distributions, model uncertainty, variable selection and functional data analysis.

- Bioinformatics, statistical genetics and medical statistics

Research covers bioinformatics (eg DNA microarray data), involving collaboration with the School of Biosciences. Other interests include population genetics, clinical trials and survival analysis.

- Nonparametric statistics

Research focuses on empirical likelihood, high-dimensional data analysis, nonlinear dynamic analysis, semi-parametric modelling, survival analysis, risk insurance, functional data analysis, spatial data analysis, longitudinal data analysis, feature selection and wavelets.

Careers

Students often go into careers as professional statisticians in industry, government, research and teaching but our programmes also prepare you for careers in other fields requiring a strong statistical background. You have the opportunity to attend careers talks from professional statisticians working in industry and to attend networking meetings with employers.

Recent graduates have started careers in diverse areas such as the pharmaceutical industry, financial services and sports betting.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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