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Masters Degrees (Statistical Genetics)

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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. Read more

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
Research Proposal
Dissertation

Option courses:

Statistics and Data Analysis Molecular Phylogenetics Bioinformatics Molecular Evolution Genetics of Human Complex Traits Quantitative Genetic Models Functional Genomic Technologies Evolution and Climate Change 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.

Read less
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. Read more

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 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
Dissertation.

Option courses:

Statistics and Data Analysis
Molecular Phylogenetics
Bioinformatics
Molecular Evolution
Quantitative Genetic Models
Functional Genomic Technologies
Evolution and Climate Change
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
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. Read more

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
Linkage and Association in Genome Analysis
Animal Genetic Improvement
Research Proposal
Dissertation

Option courses:

Statistics and Data Analysis
Molecular Phylogenetics
Bioinformatics
Molecular Evolution
Genetics of Human Complex Traits
Quantitative
Genetic Models
Functional Genomic Technologies
Evolution and
Climate Change; Animal Genetic Improvement
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.

Read less
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. Read more
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.
-The University of Glasgow’s School of Mathematics and Statistics is ranked 4th in Scotland (Complete University Guide 2015).
-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.
-With a 94% overall student satisfaction in the National Student Survey 2014, the School of Mathematics and Statistics combines both teaching excellence and a supportive learning environment.

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

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.

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

Why this programme

-The University of Glasgow’s School of Mathematics and Statistics is ranked 4th in Scotland (Complete University Guide 2015).
-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.
-With a 94% overall student satisfaction in the National Student Survey 2014, the School of Mathematics and Statistics combines both teaching excellence and a supportive learning environment.

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.

Read less
This Masters in Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics. Read more
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.
-The University of Glasgow’s School of Mathematics and Statistics is ranked 4th in Scotland (Complete University Guide 2015).
-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.
-With a 94% overall student satisfaction in the National Student Survey 2014, the School of Mathematics and Statistics combines both teaching excellence and a supportive learning environment.

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

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.

Read less
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). Read more
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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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. Read more

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...



Read less
This MSc has a strong theoretical and methodological component to supplement a focus on applications of statistics to real life scientific problems. Read more
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

Read less
The MSc in Statistics at the University of Leeds is a flexible degree programme enabling students from a wide range of backgrounds to both broaden and deepen their understanding of statistics and maths. Read more
The MSc in Statistics at the University of Leeds is a flexible degree programme enabling students from a wide range of backgrounds to both broaden and deepen their understanding of statistics and maths. It is accredited by the Royal Statistical Society and completion of the programme will qualify students for the status of 'Graduate Statistician'- the first stage towards Chartered Statistician status.

The programme provides training in a range of statistical techniques (and transferable skills) suitable for either careers in statistics and research-related professions, or for further academic research in statistics.

Options within the course vary from mainstream topics in statistical methodology to more specialised areas and reflects specific research interests of academic staff with the department - examples include statistical shape analysis, directional data, statistical genetics and stochastic financial modelling.

The course consists of two semesters of taught modules, with the third semester devoted to a major dissertation. Within each semester there is one compulsory module. However, students tailor the course to meet their individual needs through selection of a further three modules from a variety of options. This selection means a student can specialise in biological or financial applications of statistics or retain a broad base of statistical expertise.

Why study for an MSc in Statistics?

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.

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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. Read more
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. Read more
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.
-The University of Glasgow’s School of Mathematics and Statistics is ranked 4th in Scotland (Complete University Guide 2015).
-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.
-With a 94% overall student satisfaction in the National Student Survey 2014, the School of Mathematics and Statistics combines both teaching excellence and a supportive learning environment.

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.

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.

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.

Read less
International Master's in Statistics - MSc. https://www.kent.ac.uk/courses/postgraduate/163/international-masters-statistics. Read more
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. Read more
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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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). Read more
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). 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:
-Have first class knowledge and capabilities for a career in life science research and in expert duties in the public and private sectors.
-Competence to work as a member of a group of experts.
-Have understanding of the regulatory and ethical aspects of scientific research.
-Have excellent communication and interpersonal skills for employment in an international and interdisciplinary professional setting.
-Understand the general principles of mathematical modelling, computational, probabilistic and statistical analysis of biological data, and be an expert in one specific specialisation area of the LSI programme.
-Understand the logical reasoning behind experimental sciences and be able to critically assess research-based information.
-Have mastered scientific research, making systematic use of investigation or experimentation to discover new knowledge.
-Have the ability to report results in a clear and understandable manner for different target groups.
-Have good opportunities to continue your studies for a doctoral degree.

The University of Helsinki will introduce annual tuition fees to foreign-language Master’s programmes starting on August 1, 2017 or later. The fee ranges from 13 000-18 000 euros. Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area, are liable to these fees. You can check this FAQ at the Studyinfo website whether or not you are required to pay tuition fees: https://studyinfo.fi/wp2/en/higher-education/higher-education-institutions-will-introduce-tuition-fees-in-autumn-2017/am-i-required-to-pay-tuition-fees/

Programme Contents

The Life Science Informatics Master’s Programme has six specialisation areas, each anchored in its own research group or groups.

Algorithmic Bioinformatics
Goes 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
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.

Selection of the Major

During the first Autumn semester, each specialisation area gives you an introductory course. At the beginning of the Spring semester you are assumed to have decided your study direction.

Programme Structure

Studies amount to 120 credits (ECTS), which can be completed in two years according to a personal study plan.
-60 credits of advanced studies from the specialisation area, including a Master’s thesis, 30 credits.
-60 credits of other studies chosen from the programme or from other programmes (e.g. computer science, mathematics and statistics, genetics, ecology and evolutionary biology).

Internationalization

The Life Science Informatics MSc is an international programme, with international students and an international research environment. The researchers and professors in the programme are internationally recognized for their research. A significant fraction of the teaching and research staff is international.

As a student you can participate in an international student exchange programme, which offers the possibility to include international experience as part of your degree. Life Science Informatics itself is an international field and graduates can find employment in any country.

In the programme, all courses are given in English. Although the Helsinki region is very international and English is widely spoken, you can also take courses to learn Finnish via the University of Helsinki’s Language Centre’s Finnish courses. The Language Centre also offers an extensive programme of foreign language courses for those interested in learning new languages.

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