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Masters Degrees (Bioinformatics And Systems Biology)

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Our MSc Bioinformatics and Systems Biology course looks at two concepts that complement each other and reflect the skills currently sought by employers in academia and industry. Read more

Our MSc Bioinformatics and Systems Biology course looks at two concepts that complement each other and reflect the skills currently sought by employers in academia and industry.

Bioinformatics is changing as high throughput biological data collection becomes more systems-oriented, with employers seeking people who can work across both disciplines.

Enormous success has been achieved in bioinformatics, such as in defining homologous families of sequences at the DNA, RNA, and protein levels. However, our appreciation of function is changing rapidly as experimental analysis scales up to cellular and organismal viewpoints. 

At these levels, we are interested in the properties of a network of interacting components in a system, as well as the components themselves. 

Our MSc reflects these exciting developments, providing an integrated programme taught by researchers at the forefront of fields spanning bioinformatics, genomics and systems biology.

You will gain theoretical and practical knowledge of methods to analyse and interpret the data generated by modern biology. This involves the appreciation of biochemistry and molecular biology, together with IT and computer science techniques that will prepare you for multidisciplinary careers in research.

Aims

This course aims to:

  • provide a biological background to the data types of genomics, proteomics and metabolomics;
  • develop the computational and analytical understanding necessary as a platform for processing biological data;
  • demonstrate applications and worked examples in the fields of bioinformatics and system biology, integrating with student involvement through project work.

Special features

Expert teaching

Learn from researchers at the forefront of fields spanning bioinformatics, genomics and systems biology.

Research experience

Develop your research skills in preparation for a career in the biosciences industry or academic research.

Teaching and learning

We use a range of teaching and learning methods, including lectures, practicals, group discussions, problem classes and e-learning.

Research projects provide experience of carrying out a substantive research project, including the planning, execution and communication of original scientific research.

Find out more by visiting the postgraduate teaching and learning page.

Coursework and assessment

Research projects are assessed by written report. Taught units are assessed through both coursework and exams.

Course unit details

The taught part of the course runs from September to April and consists of 60 credits delivered from four 15-credit units:

  • Bioinformatics
  • Programming Skills
  • Computational Approaches to Biology
  • Experimental Design and Statistics.

You will undertake two research projects, each carrying 60 credits, in Semester 2 and the summer.

Additionally, tutorials and the Graduate Training Programme (skills development) will run through the whole course.

What our students say

"My final MSc project was conducted in collaboration with a cancer research group in Liverpool, aimed at facilitating targeted DNA sequencing of gene regions identified as being important for breast cancer.

This gave me an opportunity to work together with researchers outside of the university on a project that had real-world value."

Martin Gerner

Facilities

You will be able to access a range of facilities throughout the University.

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service .

Career opportunities

Our graduates acquire a wide range of subject-specific and transferable skills and extensive research experience.

The combination of systems biology and bioinformatics addressed in this course reflects the current skills sought in academic and industrial (eg pharmaceutical) settings.

Around half of each class find PhD positions straight after the MSc, while others build upon their training to enter careers in biology and IT.



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The MSc in Bioinformatics and Computational Biology at UCC is a one-year taught masters course commencing in September. Bioinformatics is a fast-growing field at the intersection of biology, mathematics and computer science. Read more
The MSc in Bioinformatics and Computational Biology at UCC is a one-year taught masters course commencing in September. Bioinformatics is a fast-growing field at the intersection of biology, mathematics and computer science. It seeks to create, advance and apply computer/software-based solutions to solve formal and practical problems arising from the management and analysis of very large biological data sets. Applications include genome sequence analysis such as the human genome, the human microbiome, analysis of genetic variation within populations and analysis of gene expression patterns.

As part of the MSc course, you will carry out a three month research project in a research group in UCC or in an external university, research institute or industry. The programming and data handling skills that you will develop, along with your exposure to an interdisciplinary research environment, will be very attractive to employers. Graduates from the MSc will have a variety of career options including working in a research group in a university or research institute, industrial research, or pursuing a PhD.

Visit the website: http://www.ucc.ie/en/ckr33/

Course Detail

This MSc course will provide theoretical education along with practical training to students who already have a BSc in a biological/life science, computer science, mathematics, statistics, engineering or a related degree.

The course has four different streams for biology, mathematics, statistics and computer science graduates. Graduates of related disciplines, such as engineering, physics, medicine, will be enrolled in the most appropriate stream. This allows graduates from different backgrounds to increase their knowledge and skills in areas in which they have not previously studied, with particular emphasis on hands-on expertise relevant to bioinformatics:

- Data analysis: basic statistical concepts, probability, multivariate analysis methods
- Programming/computing: hands-on Linux skills, basic computing skills and databases, computer system organisation, analysis of simple data structures and algorithms, programming concepts and practice, web applications programming
- Bioinformatics: homology searches, sequence alignment, motifs, phylogenetics, protein folding and structure prediction
- Systems biology: genome sequencing projects and genome analysis, functional genomics, metabolome modelling, regulatory networks, interactome, enzymes and pathways
- Mathematical modelling and simulation: use of discrete mathematics for bioinformatics such as graphs and trees, simulation of biosystems
- Research skills: individual research project, involving a placement within the university or in external research institutes, universities or industry.

Format

Full-time students must complete 12 taught modules and undertake a research project. Part-time students complete about six taught modules in each academic year and undertake the project in the second academic year. Each taught module consists of approximately 20 one-hour lectures (roughly two lectures per week over one academic term), as well as approximately 10 hours of practicals or tutorials (roughly one one-hour practical or tutorial per week over one academic term), although the exact amount of lectures, practicals and tutorials varies between individual modules.

Assessment

There are exams for most of the taught modules in May of each of the two academic years, while certain modules may also have a continuous assessment element. The research project starts in June and finishes towards the end of September. Part-time students will carry out their research project during the summer of their second academic year.

Careers

Graduates of this course offer a unique set of interdisciplinary skills making them highly attractive to employers at universities, research centres and in industry. Many research institutes have dedicated bioinformatics groups, while many 'wet biology' research groups employ bioinformaticians to help with data analyses and other bioinformatics problems. Industries employing bioinformaticians include the pharmaceutical industry, agricultural and biotechnology companies. For biology graduates returning to 'wet lab' biology after completing the MSc course, your newly acquired skills will be extremely useful. Non-biology graduates seeking non-biology positions will also find that having acquired interdisciplinary skills is of great benefit in getting a job.

How to apply: http://www.ucc.ie/en/study/postgrad/how/

Funding and Scholarships

Information regarding funding and available scholarships can be found here: https://www.ucc.ie/en/cblgradschool/current/fundingandfinance/fundingscholarships/

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This Masters in Bioinformatics (formerly Bioinformatics, Polyomics and Systems Biology) is an exciting and innovative programme that has recently been revamped. Read more

This Masters in Bioinformatics (formerly Bioinformatics, Polyomics and Systems Biology) is an exciting and innovative programme that has recently been revamped. Bioinformatics is a discipline at the interface between biology, computing and statistics and is used in organismal biology, molecular biology and biomedicine. This programme focuses on using computers to glean new insights from DNA, RNA and protein sequence data and related data at the molecular level through data storage, mining, analysis and graphical presentation - all of which form a core part of modern biology.

Why this programme

  • Our programme emphasises understanding core principles in practical bioinformatics and functional genomics, and then implementing that understanding in a series of practical elective courses in semester 2 and in a summer research project.
  • You will benefit from being taught by scientists at the cutting edge of their field and you will get intensive, hands-on experience in an active research lab during the summer research project.
  • Bioinformatics and the 'omics' technologies have evolved to play a fundamental role in almost all areas of biology and biomedicine.
  • Advanced biocomputing skills are now deemed essential for many PhD studentships/projects in molecular bioscience and biomedicine, and are of increasing importance for many other such projects.
  • The semester 2 courses are built around real research scenarios, enabling you not only to gain practical experience of working with large molecular datasets, but also to see why each scenario uses the particular approaches it does and how to go about organising and implementing appropriate analysis pipelines.
  • You will be based in the College of Medical, Veterinary & Life Sciences, an ideal environment in which to train in bioinformatics. Our College has carried out internationally-leading research in functional genomics and systems biology.
  • Some of the teaching and research scenarios you’ll be exposed to reflect the activities of 'Glasgow Polyomics', a world-class omics facility set up within the university in 2012 to provide research services using microarray, proteomics, metabolomics and next-generation DNA sequencing technologies. Its' scientists have pioneered the 'polyomics' approach, in which new insights come from the integration of data across different omics levels.
  • In addition, we have several world-renowned research centres at the University, such as the Wellcome Centre for Molecular Parasitology, the MRC-University of Glasgow Centre for Virus Research and the Wolfson Wohl Cancer Research Centre, whose scientists do ground-breaking research employing bioinformatic approaches in the study of disease.
  • You will learn computer programming in courses run by staff in the internationally reputed School of Computing Science, in conjunction with their MSc in Information Technology.

Programme structure

Bioinformatics helps biologists gain new insights about genomes (genomics) and genes, about RNA expression products of genes (transcriptomics) and about proteins (proteomics); rapid advances have also been made in the study of cellular metabolites (metabolomics) and in a newer area, systems biology.

‘Polyomics’ is an intrinsically systems-level approach involving the integration of data from these ‘functional genomics’ areas - genomics, transcriptomics, proteomics and metabolomics - to derive new insights about how biological systems function.

The programme structure is designed to equip students with understanding and hands-on experience of both computing and biological research practices relating to bioinformatics and functional genomics, to show students how the computing approaches and biological questions they are being used to answer are connected, and to give students an insight into new approaches for integration of data and analysis across the 'omics' domains.

On this programme, you will develop a range of computing and programming skills, as well as skills in data handling, analysis (including statistics) and interpretation, and you will be brought up to date with recent advances in biological science that have been informed by bioinformatics approaches.

The programme has the following overall structure

  • core material of 60 credits in semester 1, made up of 10, 15 and 20 credit courses.
  • optional material of 60 credits in semester 2: students select 4 courses (two 10 credit courses and two 20 credit courses) from those available.
  • Project of 60 credits over 14 weeks embedded in a research group over the summer.

Additional information about the programme can be found in the Bioinformatics MSc Programme Structure 2017-18.

Please note: students undertaking the three month PgCert will also be required to take two exams in March/April.

Career prospects

Most of our graduates embark on a University or Institute-based research career path, here in the UK or abroad, using the skills they've acquired on our programme. These skills are now of primary relevance in many areas of modern biology and biomedicine. Many are successful in getting a PhD studentship. Others are employed as a core bioinformatician (now a career path within academia in its own right) or as a research assistant in a research group in basic biological or medical science.

A postgraduate degree in bioinformatics is also valued by many employers in the life sciences sector - eg computing biology jobs in biotechnology, biosciences, neuroinformatics and the pharma industries.

Some of our graduates have entered science-related careers in scientific publishing or education. Others have gone into computing-related jobs in non-bioscience industry or the public sector.



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This course provides specialist skills in core systems biology with a focus on the development of computational and mathematical research skills. Read more

This course provides specialist skills in core systems biology with a focus on the development of computational and mathematical research skills. It specialises in computational design, providing essential computing and engineering skills that allow you to develop software to program biological systems.

This interdisciplinary course is based in the School of Computing Science and taught jointly with the Faculty of Medical Sciences and the School of Mathematics and Statistics. The course is ideal for students aiming for careers in industry or academia. We cater for students with a range of backgrounds, including Life Sciences, Computing Science, Mathematics and Engineering.

Computational Systems Biology is focused on the study of organisms from a holistic perspective. Computational design of biological systems is essential for allowing the construction of complex and large biological systems.

We provide a unique, multidisciplinary experience essential for understanding systems biology. The course draws together the highly-rated teaching and research expertise of our Schools of Computing Science, Mathematics and Statistics, Biology, and Cell and Molecular Biosciences. The course also has strong links with Newcastle's Centre for Integrated Systems Biology of Ageing and Nutrition (CISBAN).

Our course is designed for students from both biological and computational backgrounds. Prior experience with computers or computer programming is not required. Students with mathematical, engineering or other scientific backgrounds are also welcome to apply.

The course is part of a suite of related programmes that also include:

-Bioinformatics MSc

-Synthetic Biology MSc

-Computational Neuroscience and Neuroinformatics MSc

All four programmes share core modules, creating a tight-knit cohort. This encourages collaborations on projects undertaking interdisciplinary research.

Project work

Your five month research project gives you a real opportunity to develop your knowledge and skills in depth in Systems Biology. You have the opportunity to work closely with a leading research team in the School and there are opportunities to work on industry lead projects. You will have one-to-one supervision from an experienced member of the faculty, supported with supervision from associated senior researchers and industry partners as required.

The project can be carried out:

-With a research group at Newcastle University

-With an industrial sponsor

-With a research institute

-At your place of work

Placements

Students have a unique opportunity to complete a work placement with one of our industrial partners as part of their projects.

Previous students have found placements with organisations including:

-NHS Business Services Authority

-Waterstons

-Metropolitan Police

-Accenture

-IBM

-Network Rail

-Nissan

-GSK

Accreditation

We have a policy of seeking British Computer Society (BCS) accreditation for all of our degrees, so you can be assured that you will graduate with a degree that meets the standards set out by the IT industry. Studying a BCS-accredited degree provides the foundation for professional membership of the BCS on graduation and is the first step to becoming a chartered IT professional.

The School of Computing Science at Newcastle University is an accredited and a recognised Partner in the Network of Teaching Excellence in Computer Science.

Facilities

Facilities

You will have dedicated computing facilities in the School of Computing. You will have access to the latest tools for system analysis and development. For certain projects, special facilities for networking can be set up.

You will enjoy access to specialist IT facilities to support your studies, including:

  • a dedicated virtual Linux workstation
  • a dedicated virtual Windows workstation
  • high specification computers only for postgrduates
  • over 300 PC's running Windows, 120 just for postgraduates
  • over 300 Raspberry Pi devices 
  • high-performance supercomputers
  • the latest Windows operating system and development tools
  • 27" monitors with high resolution (2560X1440) display
  • high-capacity database servers
  • motion capture facilities
  • 3D printing facilities

You will have access to a Linux based website that you can customise with PHP hosting services.

We have moved to the new £58m purpose-built Urban Sciences Building. Our new building offers fantastic new facilities for our students and academic community. The building is part of Science Central, a £350 million project bringing together:

  • academia
  • the public sector
  • communities
  • business and industry.


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We offer an opportunity to train in one of the newest areas of biology. the application of engineering principles to the understanding and design of biological networks. Read more

We offer an opportunity to train in one of the newest areas of biology: the application of engineering principles to the understanding and design of biological networks. This new approach promises solutions to some of today’s most pressing challenges in environmental protection, human health and energy production.

This MSc will provide you with a thorough knowledge of the primary design principles and biotechnology tools being developed in systems and synthetic biology, ranging from understanding genome-wide data to designing and synthesising BioBricks.

You will learn quantitative methods of modelling and data analysis to inform and design new hypotheses based on experimental data. The University’s new centre, SynthSys, is a hub for world-leading research in both systems and synthetic biology.

Programme structure

The programme consists of two semesters of taught courses followed by a research project and dissertation, which can be either modelling-based or laboratory-based.

Compulsory courses:

  • Information Processing in Biological Cells
  • Social Dimensions of Systems and Synthetic Biology
  • Dissertation project
  • Practical Systems Biology
  • Applications of Synthetic Biology
  • Tools for Synthetic Biology

Option courses:

  • Neural Computation
  • Probabilistic Modelling and Reasoning
  • Functional Genomic Technologies
  • Bioinformatics Programming & System Management
  • Stem Cells & Regenerative Medicine
  • Statistics and Data Analysis
  • Biobusiness
  • Gene Expression & Microbial Regulation
  • Bioinformatics Algorithms
  • Biological Physics
  • Computational Cognitive Neuroscience
  • Molecular Phylogenetics
  • Next Generation Genomics
  • Drug Discovery
  • Biochemistry A & B
  • Environmental Gene Mining & Metagenomics
  • Economics & Innovation in the Biotechnology Industry
  • Industry & Entrepreneurship in Biotechnology
  • Introduction to Scientific Programming
  • Practical Skills in Biochemistry A & B
  • Mathematical Biology

Career opportunities

The programme is designed to give you a good basis for managerial or technical roles in the pharmaceutical and biotech industries. It will also prepare you for entry into a PhD programme.



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Cell-to-cell signalling in development and disease. Do you have a clear and specific interest in cancer, stem cells or developmental biology? Our Master’s programme. Read more

Cell-to-cell signalling in development and disease

Do you have a clear and specific interest in cancer, stem cells or developmental biology? Our Master’s programme Cancer, Stem Cells and Developmental Biology combines research in three areas: oncology, molecular developmental biology and genetics. The focus is on molecular and cellular aspects of development and disease, utilising different model systems (mice, zebrafish, C. elegans, organoids and cell lines). The programme will guide you through the mysteries of embryonic growth, stem cells, signalling, gene regulation, evolution, and development as they relate to health and disease.

The right choice for you?

Given that fundamental developmental processes are so often impacted by disease, an understanding of these processes is vital to the better understanding of disease treatment and prevention. Adult physiology is regulated by developmental genes and mechanisms which, if deregulated, may result in pathological conditions. If you have a specific interest in cancer, stem cells or developmental biology, this Master’s programme is the right choice for you. Cancer, Stem Cells and Developmental Biology offers you international, high ranked research training and education that builds on novel methodology in genomics, proteomics, metabolomics and bioinformatics technology applied to biomedical and developmental systems and processes.

What you’ll learn

In the Cancer, Stem Cells and Developmental Biology programme you will learn to focus on understanding processes underlying cancer and developmental biology using techniques and applications of post-genomic research, including microarray analysis, next generation sequencing, proteomics, metabolomics and advanced microscopy techniques. You explore research questions concerning embryonic growth, stem cells, signaling pathways, gene regulation, evolution and development in relation to health and disease using various model systems. As a Master’s student you will take theory courses and seminars, as well as master classes led by renowned specialists in the field. The courses are interactive, and challenge you to further improve your writing and presenting skills.

Why study Cancer, Stem Cells and Developmental Biology at Utrecht University?

Compared to most other Master’s programmes in cancer and stem cell biology in the Netherlands, in Utrecht we offer:

  • Strong focus on fundamental molecular aspects of disease related questions, particularly questions related to cancer and the use of stem cells in regenerative medicine
  • A unique emphasis on Developmental Biology, a process with many connections to cancer
  • The opportunity to carry out two extensive research projects at renowned research groups
  • An intensive collaboration with national and international research institutes, allowing you to do your internship at prestigious partner institutions all around the world

Career in Cancer, Stem Cells and Developmental Biology

As a MSc graduate trained in both fundamental and disease-oriented aspects of biomedical genetics you are in great demand. You’ll be prepared for PhD study in one of the participating or associated groups. Alternatively, leaving after obtaining your MSc degree you will profit from a solid education in molecular genetics, in addition to your specialised knowledge of developmental biology. You’ll find your way to biotechnology, the pharmaceutical industry or education.



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If you have a Bachelors degree in the biosciences, biochemistry, pharmacy or biological chemistry and you want to develop specialist knowledge in molecular biology then this postgraduate programme is for you. Read more
If you have a Bachelors degree in the biosciences, biochemistry, pharmacy or biological chemistry and you want to develop specialist knowledge in molecular biology then this postgraduate programme is for you. It will allow you to gain new skills and enhance your employability in the pharmaceutical and biotechnology industries or allow you to progress to a research degree.

About the course

The MSc Molecular Biology will give you hands on practical experience of both laboratory and bioinformatics techniques. You will also be trained in molecular biology research strategies. A strong practical foundation is provided in the first semester (Semester A) when you will study two modules:
-Cellular Molecular Biology - This module aims to help you develop a systematic understanding and knowledge of recombinant DNA technology, bioinformatics and associated research methodology.
-Core Genetics and Protein Biology - This module will provide you with an advanced understanding of genetics, proteins, the area of proteomics and the molecular basis of cellular differentiation and development.

The second semester (Semester B) has a problem-based learning approach to the application of the knowledge you gained in Semester A. You will study two modules:
-Molecular Medicine - You will study the areas of protein design, production and engineering, investigating specific examples of products through the use of case studies.
-Molecular Biotechnology - You will gain an in-depth understanding of the application of molecular biological approaches to the characterisation of selected diseases and the design of new drugs for their treatment.

In semester C you will undertake a research project to develop your expertise further. The research project falls into different areas of molecular biology and may include aspects of fermentation biotechnology, cardiovascular molecular biology, cancer, angiogenesis research, diabetes, general cellular molecular biology, bioinformatics, microbial physiology and environmental microbiology.

Why choose this course?

-This course gives in-depth knowledge of molecular biology for biosciences graduates
-It has a strong practical basis giving you training in molecular biology research strategies and hand-on experience of laboratory and bioinformatics techniques
-It equips you for research and development positions in the biotechnology and pharmaceutical industries, as well as a wide range of non-research roles in industry
-Biosciences research facilities cover fermentation biotechnology, high performance liquid chromatography, (HPLC), cell culture, molecular biology and pharmacology
-There are excellent facilities for chemical and biomedical analysis, genetics and cell biology studies and students have access to the latest equipment for PCR, qPCR and 2D protein gel analysis systems for use during their final year projects
-The School of Life and Medical Science will move into a brand new science building opening in September 2016 providing us with world class laboratories for our teaching and research. At a cost of £50M the new building provides spacious naturally lit laboratories and social spaces creating an environment that fosters multi-disciplinary learning and research

Careers

Graduates of the programme will be qualified for research and development positions in the pharmaceutical and biotechnology industries, to progress to a research degree, or to consider non-research roles in industry such as management, manufacturing and marketing.

Teaching methods

The course consists of five modules including a research project. All modules are 100% assessed by coursework including in-class tests.
-Cellular Molecular Biology
-Core Genetics and Protein Biology
-Molecular Biotechnology
-Molecular Medicine Research
-Biosciences Research Methods for Masters
-Methods and Project

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What is the Master of Bioinformatics all about?.  Bioinformaticians are distinguished by their ability to formulate biologically relevant questions, design and implement the appropriate solution by managing and analysing high-throughput molecular biological and sequence data, and interpret the obtained results. Read more

What is the Master of Bioinformatics all about?

 Bioinformaticians are distinguished by their ability to formulate biologically relevant questions, design and implement the appropriate solution by managing and analysing high-throughput molecular biological and sequence data, and interpret the obtained results.

Structure

This interdisciplinary two-year programme focuses on acquiring

  • basic background knowledge in diverse disciplines belonging to the field of bioinformatics, including statistics, molecular biology and computer science
  • expert knowledge in the field of bioinformatics
  • programming skills
  • engineering skills

The 120-credit programme consists of a reorientation package (one semester), a common package (two semesters) and a thesis.

The Master of Bioinformatics is embedded in a strong bioinformatics research community in KU Leuven, who monthly meet at the Bioinformatics Interest Group. Bioinformatics research groups are spread over the Arenberg and Gasthuisberg campus and are located in the research departments of Microbial and Molecular Systems (M2S), Electrical Engineering (ESAT), Human Genetics, Microbiology and Immunology (REGA), Cellular and Molecular Medicine, Chemistry and Biology. Several of these bioinformatics research groups are also associated with the Flemish Institute for Biotechnology (VIB).

Is this the right programme for me? 

Are you a biochemist or molecular biologist with a keen interest in mathematics and programming? Are you a mathematician or statistician and want to apply your knowledge to complex biological questions? Do you want to develop new methods that can be used by doctors, biologists and biotechnology engineers? Then this is the right program for you!

Objectives

The student:

  • Possesses a broad knowledge of the principles of genetics, biochemistry and molecular and cellular biology that underlie the model systems, the experimental techniques, and the generation of data that are analysed and modelled in bioinformatics.
  • Possesses a broad knowledge of the basic mathematical disciplines (linear algebra, calculus, dynamical systems) that underlie mathematical and statistical modelling in bioinformatics.
  • Masters the concepts and techniques from information technology (database management, structured and object-oriented programming, semantic web technology) for the management and analysis of large amounts of complex and distributed biological and biomedical data.
  • Masters the concepts and techniques from machine learning and frequentist and Bayesian statistics that are used to analyse and model complex omics data.
  • Has acquired knowledge of the core methods of computational biology (such as sequence analysis, phylogenetic analysis, quantitative genetics, protein modelling, array analysis).
  • Has advanced interdisciplinary skills to communicate with experts in life sciences, applied mathematics, statistics, and computer science to formalise complex biological problems into appropriate data management and data analysis strategies.
  • Can - in collaboration with these experts - design complex omics experiments and analyse them independently.
  • Can independently collect and manage data from specialised literature and public databases and critically analyse and interpret this data to solve complex research questions, as well as develop tools to support these processes.
  • Investigates and understands interaction with other relevant science domains and integrate them within the context of more advanced ideas and practical applications and problem solving.
  • Demonstrates critical consideration of and reflection on known and new theories, models or interpretation within the specialty; and can efficiently adapt to the rapid evolution the life sciences, and especially in omics techniques, by quickly learning or developing new analysis strategies and incorporating them into the learned competences.
  • Presents personal research, thoughts, ideas, and opinions of proposals within professional activities in a suitable way, both written and orally, to peers and to a general public.
  • Develop and execute original scientific research and/or apply innovative ideas within research units.
  • Understands ethical, social and scientific integrity issues and responsibilities and is able to analyse the local and global impact of bioinformatics and genomics on individuals, organisations and society.

Career paths

Bioinformaticians find careers in the life sciences domain in the broadest sense: industry, the academic world, health care, etc. The expanding need for bioinformatics in biological and medical research ensures a large variety of job opportunities in fundamental and applied research. 60% of our graduates start a PhD after graduation.

 



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Applications are invited for the MSc in Bioinformatics and Theoretical Systems. Biology. The programme will provide an interdisciplinary training and applications. Read more
Applications are invited for the MSc in Bioinformatics and Theoretical Systems
Biology. The programme will provide an interdisciplinary training and applications
are invited from students graduating from any biological, physical, computational
or mathematical first degree course. We are keen to encourage graduates from
numerical and physical sciences to join the course.

This programme will provide students with the necessary skills to produce effective
research in Bioinformatics and Systems Biology. The course, which is based at the
South Kensington campus, has been designed and is taught by staff from the Faculties
Natural Sciences, Engineering (Computing) and Medicine.

In the first term, students take the following courses:
• Bioinformatics and Systems Biology - Introduction to biology; advanced tools for the
analysis of biological data; and approaches for modelling biological systems
• Computing - Python, R, & Unix
• Mathematics & statistical inference - high level algorithms & analysis of large datasets

The remainder of the year is devoted to three full-time research projects,
undertaken under the supervision of researchers at Imperial College.

Wellcome Trust 4 year PhD Programme

Please note there is also a separate funded 4 year PhD programme, supported by the Wellcome Trust, which starts with this Master’s course and then progresses to a three year PhD. The closing date for application is Monday 5 December 2016 for admission in October 2017. Details, including how to apply, can be found at

http://www.imperial.ac.uk/wellcome-bioinformatics-phd/

Applicants must have or be expected to obtain at least an upper second honours
degree or an equivalent overseas qualification. Please be aware that we do not
do any 'wet lab' research as part of our courses, it is purely computer based. If you
are not an EU citizen, we do not have any finance for our MSc. For further details and the application procedure
see:

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The Bioinformatics MSc combines foundational skills in bioinformatics with specialist skills in computing programming, molecular biology and research methods. Read more

The Bioinformatics MSc combines foundational skills in bioinformatics with specialist skills in computing programming, molecular biology and research methods. Our unique, interdisciplinary course draws together highly-rated teaching and research expertise from across the University, equipping you for a successful career in the bioinformatics industry or academia.

This interdisciplinary course is based in the School of Computing Science and taught jointly with the School of Biology, School of Mathematics and Statistics, Institute of Cell and Molecular Biosciences and the Institute of Genetic Medicine. It is designed for students from both biological science and computational backgrounds. Prior experience with computer programming is not required and we welcome applications from students with mathematical, engineering or other scientific backgrounds.

Our graduates have an excellent record of finding employment (around 90%). Recent examples have included:

-Bioinformatician at the Medical Research Council

-Technical consultant at Accenture

-Bioinformatics technician at Barcelona Supercomputing Centre.

Our course structure is highly flexible and you can tailor it to your own skills and interests. Half of the course is taught and the remainder is dedicated to a research project.

As research is a large component of this course, our emphasis is on delivering the research training you will need to meet the demands of industry and academia now and in the future. Our research in bioinformatics, life sciences, computing and mathematics is internationally recognised. We have an active research community, comprising several research groups and three research centres.

You will be taught by academics who are successful researchers in their field and publish regularly in highly-ranked bioinformatics journals. Our experienced and helpful staff will be happy to offer support with all aspects of your course from admissions to graduation and developing your career.

The course is part of a suite of related programmes that include:

-Synthetic Biology MSc

-Computational Neuroscience and Neuroinformatics MSc

-Computational Systems Biology MSc

All four courses share core modules. This creates a tight-knit cohort that has encouraged collaborations on projects undertaking interdisciplinary research.

Delivery

Semester one combines bioinformatics theory and application with the computational and modelling skills necessary to undertake more specialist modules in semester two. We provide training in mathematics and statistics and, for those without a biological first degree, we will also provide molecular biology training. Some of these modules are examined in January at the end of semester one.

Semester two begins with two modules that focus heavily on introducing subject-specific research skills. These two modules run sequentially, in a short but intensive mode that allows you time to focus on a single topic in depth. In the first of the second semester modules you learn how to analyse data arising from post-genomic studies such as microarray analysis, proteomic analysis and RNAseq. All of the semester two modules are examined by in-course assessment - there are no formal examinations in these modules.

Project work

Your five month project gives you an opportunity to develop your knowledge and skills in depth, and to work in a research or development team. You will have one-to-one supervision from an experienced member of staff, supported with supervision from industry partners as required.

The project can be carried out:

-With a research group at Newcastle University

-With an industrial sponsor

-With a research institute

-At your place of work.

Accreditation

We have a policy of seeking British Computer Society (BCS) accreditation for all of our degrees, so you can be assured that you will graduate with a degree that meets the standards set out by the IT industry. Studying a BCS-accredited degree provides the foundation for professional membership of the BCS on graduation and is the first step to becoming a chartered IT professional.

The School of Computing Science at Newcastle University is an accredited and a recognised Partner in the Network of Teaching Excellence in Computer Science.



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Researchers in the School of Biological Sciences conduct cutting-edge research across a broad range of biological disciplines. genomics, biotechnology, cell biology, sensory biology, animal behaviour and evolution, population biology, host-disease interactions and ecosystem services, to name but a few. Read more
Researchers in the School of Biological Sciences conduct cutting-edge research across a broad range of biological disciplines: genomics, biotechnology, cell biology, sensory biology, animal behaviour and evolution, population biology, host-disease interactions and ecosystem services, to name but a few.

In 2014 the school relocated to a new £54 million, state-of-the-art Life Sciences building. Our new laboratory facilities are among the best in the world, with critical '-omics' technologies and associated computing capacity (bioinformatics) a core component. The new building is designed to foster our already strong collaborative and convivial environment, and includes a world-leading centre for evolutionary biology research in collaboration with key researchers from earth sciences, biochemistry, social medicine, chemistry and computer sciences. The school has strong links with local industry, including BBC Bristol, Bristol Zoo and the Botanic Gardens. We have a lively, international postgraduate community of about 150 research students. Our stimulating environment and excellent graduate school training and support provide excellent opportunities to develop future careers.

Research groups

The underlying theme of our research is the search for an understanding of the function, evolution, development and regulation of complex systems, pursued using the latest technologies, from '-omics' to nanoscience, and mathematical modelling tools. Our research is organised around four main themes that reflect our strengths and interests: evolutionary biology; animal behaviour and sensory biology; plant and agricultural sciences; and ecology and environmental change.

Evolutionary Biology
The theme of evolutionary biology runs through all our research in the School of Biological Sciences. Research in this theme seeks to understand organismal evolution and biodiversity using a range of approaches and study systems. We have particular strengths in evolutionary genomics, phylogenetics and phylogenomics, population genetics, and evolutionary theory and computer modelling.

Animal Behaviour and Sensory Biology
Research is aimed at understanding the adaptive significance of behaviour, from underlying neural mechanisms ('how', or proximate, questions) to evolutionary explanations of function ('why', or ultimate, questions). The approach is strongly interdisciplinary, using diverse physiological and biomechanical techniques, behavioural experiments, computer modelling and molecular biology to link from the genetic foundations through to the evolution of behaviour and sensory systems.

Plant and Agricultural Sciences
The global issue of food security unifies research in this theme, which ranges from molecular-based analysis of plant development, signal transduction and disease, to ecological studies of agricultural and livestock production systems. We have particular strengths in functional genomics, bioinformatics, plant developmental biology, plant pathology and parasite biology, livestock parasitology and agricultural systems biology. Our research is helped by the LESARS endowment, which funds research of agricultural relevance.

Ecology and Environmental Change
Research seeks to understand ecological relations between organisms (plant, animal or microbe) at individual, population and community levels, as well as between organisms and their environments. Assessing the effect of climate change on these ecological processes is also fundamental to our research. Key research areas within this theme include community ecology, restoration ecology, conservation, evolutionary responses to climate change and freshwater ecology. Our research has many applied angles, such as ecosystem management, wildlife conservation, environmental and biological control, agricultural practice and informing policy.

Careers

Many postgraduate students choose a higher degree because they enjoy their subject and subsequently go on to work in a related area. An Office of Science and Technology survey found that around three-quarters of BBSRC- and NERC-funded postgraduates went on to a job related to their study subject.

Postgraduate study is often a requirement for becoming a researcher, scientist, academic journal editor and for work in some public bodies or private companies. Around 60 per cent of biological sciences doctoral graduates continue in research. Academic research tends to be contract-based with few permanent posts, but the school has a strong track record in supporting the careers of young researchers by helping them to find postdoctoral positions or develop fellowship applications.

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This academically challenging and career-developing programme focuses on research and development using biological and chemical principles and systems to create new products, services and industries. Read more

This academically challenging and career-developing programme focuses on research and development using biological and chemical principles and systems to create new products, services and industries.

You will employ elements of the developing field of synthetic biology to bring about significant changes and major innovations that address the challenges of rapidly changing human demographics, resource shortages, energy economy transition and the concomitant growth in demand for more and healthier food, sustainable fuel cycles, and a cleaner environment.

Programme structure

You will learn through a variety of activities, including:

  • lectures
  • workshops
  • presentations
  • laboratory work
  • field work
  • tutorials
  • seminars
  • discussion groups and project groups
  • problem-based learning activities

You will attend problem-based tutorial sessions and one-to-one meetings with your personal tutor or programme director.

You will carry out research at the frontier of knowledge and can make a genuine contribution to the progress of original research. This involves carrying out project work in a research laboratory, reviewing relevant papers, analysing data, writing reports and giving presentations.

Compulsory courses:

  • Applications of Synthetic Biology
  • Tools for Synthetic Biology
  • Social Dimensions of Systems & Synthetic Biology
  • Environmental Gene Mining & Metagenomics
  • Research Project Proposal
  • MSc Project and Dissertation

Option courses:

  • Biochemistry A & B
  • Introduction to Scientific Programming
  • Commercial Aspects of Drug Discovery
  • Stem Cells & Regenerative Medicine
  • Biological Physics
  • Enzymology & Biological Production
  • Next Generation Genomics
  • Machine Learning & Pattern Recognition
  • Drug Discovery
  • Biophysical Chemistry
  • Bioinformatics Programming & System Management
  • Economics & Innovation in the Biotechnology Industry
  • BioBusiness
  • Molecular Modelling & Database Mining
  • Industry & Entrepreneurship in Biotechnology
  • Practical Skills in Biochemistry A & B
  • Functional Genomic Technologies
  • Information Processing in Biological Cells
  • Data Mining & Exploration
  • Gene Expression & Microbial Regulation
  • Bioinformatics
  • Principles of Industrial Biotechnology

Learning outcomes

By the end of the programme you will have gained:

  • a strong background knowledge in the fields underlying synthetic biology and biotechnology
  • an understanding of the limitations and public concerns regarding the nascent field of synthetic biology including a thorough examination of the philosophical, legal, ethical and social issues surrounding the area
  • the ability to approach the technology transfer problem equipped with the skills to analyse the problem in scientific and practical terms
  • an understanding of how biotechnology relates to real-world biological problems
  • the ability to conduct practical experimentation in synthetic biology and biotechnology
  • the ability to think about the future development of research, technology, its implementation and its implications
  • a broad understanding of research responsibility including the requirement for rigorous and robust testing of theories and the need for honesty and integrity in experimental reporting and reviewing

Career opportunities

You will enhance your career prospects by acquiring current, marketable knowledge and developing advanced analytical and presentational skills, within the social and intellectual sphere of a leading European university.

The School of Biological Sciences offers a research-rich environment in which you can develop as a scientist and entrepreneur.



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Goal of the pro­gramme. 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 (. Read more

Goal of the pro­gramme

Life Sciences is one of the strategic research fields at the University of Helsinki. The multidisciplinary Master’s Programme in Life Science Informatics (LSI) integrates research excellence and research infrastructures in the Helsinki Institute of Life Sciences (HiLIFE).

The Master's Programme is offered by the Faculty of Science. Teaching is offered in co-operation with the Faculty of Medicine and the Faculty of Biological and Environmental Sciences. As a student, you will gain access to active research communities on three campuses: Kumpula, Viikki, and Meilahti. The unique combination of study opportunities tailored from the offering of the three campuses provides an attractive educational profile. The LSI programme is designed for students with a background in mathematics, computer science and statistics, as well as for students with these disciplines as a minor in their bachelor’s degree, with their major being, for example, ecology, evolutionary biology or genetics. As a graduate of the LSI programme you will:

  • 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

Further information about the studies on the Master's programme website.

Pro­gramme con­tents

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

Algorithmic bioinformatics with the Genome-scale algorithmicsCombinatorial 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 bioinformaticsjointly with The Institute of Biotechnology and genetics.Bioinformatics has become an integral part of biological research, where innovative computational approaches are often required to achieve high-impact findings in an increasingly data-dense environment. Studies in applied bioinformatics prepare you for a post as a bioinformatics expert in a genomics research lab, working with processing, analysing and interpreting Next-Generation Sequencing (NGS) data, and working with integrated analysis of genomic and other biological data, and population genetics.

Biomathematics with the Biomathematics research group, focusing on mathematical modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of topics ranging from problems at the molecular level to the structure of populations. To tackle these problems, the research group uses a variety of modelling approaches, most importantly ordinary and partial differential equations, integral equations and stochastic processes. A successful analysis of the models requires the study of pure research in, for instance, the theory of infinite dimensional dynamical systems; such research is also carried out by the group. 

Biostatistics and bioinformatics is offered jointly by the statistics curriculum, the Master´s Programme in Mathematics and Statistics and the research groups Statistical and Translational GeneticsComputational 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 BiomedicumThe 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.



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Introduced in 2004, this course was developed by the Cambridge Computational Biology Institute, an interdisciplinary centre bringing together the unique strengths of Cambridge in medicine, biology, mathematics and the physical sciences. Read more
Introduced in 2004, this course was developed by the Cambridge Computational Biology Institute, an interdisciplinary centre bringing together the unique strengths of Cambridge in medicine, biology, mathematics and the physical sciences.

The course is aimed at introducing students to quantitative aspects of biological and medical sciences. It is intended for mathematicians, computer scientists and others wishing to learn about the subject in preparation for a PhD course or a career in industry. It is also suitable for students with a first degree in biosciences as long as they have strong quantitative skills (which should be documented in the application).

This 11-month course consists of core modules in bioinformatics, scientific programming with R, genomics, systems biology and network biology. Before the start of the first term, students are required to attend an introductory course in molecular biology. Courses are delivered in association with several University departments from the Schools of Biological Sciences and Physical Sciences, groups within the School of Clinical Medicine, the European Bioinformatics Institute and the Sanger Institute. The course concludes with a three-month internship in a university or industrial laboratory.

Visit the website: http://www.graduate.study.cam.ac.uk/courses/directory/maammpcbi

Learning Outcomes

After completing the MPhil in Computational Biology, students will be expected to have:

- acquired a sound knowledge of a range of tools and methods in computational biology;
- developed the capacity for independent study and problem solving at a higher level;
- undertaken an internship project within a laboratory or group environment, and produced a project report;
- given at least one presentation on their project.

Format

The course combines taught lectures (October-April), followed by a summer internship project (May-August). There are typically 3-4 taught modules per term, and each module consists of 16 hours of lectures. Each module is assessed by coursework, and there is one general examination in May.

The Course Director is available throughout the year for individual meetings, and briefly meets termly with each student to check on progress. Each lecturer is also encouraged to arrange an office hour whereby students can talk about their progress.

Lectures: Typically 16 hours per module, with students taking 8 modules.

Journal Clubs: A weekly seminar is held during the first two terms on topics across Computational Biology. These seminars help students to select an appropriate project.

Placements

Students undertake a mandatory internship (May to August) in either a university or industrial laboratory. The Department will compile a list of possible opportunities which students can discuss directly with the host laboratory. Alternatively students may organise their own internship, subject to the approval of the Course Director.

Assessment

A 18,000 word (maximum) report must be written to summarise the student's internship. An oral presentation on this report must also be given.

Students give a 25 minute presentation on their project as part of the formal assessment. Some assessed coursework may also require students to present their work.

Each module is assessed typically by two written assignments. These assignments involve significant computational elements.

A compulsory two-hour general examination is sat in May.

Continuing

MPhil students wishing to apply for a PhD at Cambridge must apply via the Graduate Admissions Office for continuation by the relevant deadline.

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

There are no specific funding opportunities advertised for this course. For information on more general funding opportunities, please follow the link below.

General Funding Opportunities: http://www.2016.graduate.study.cam.ac.uk/finance/funding

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Introduced in 2004, this course was developed by the Cambridge Computational Biology Institute, an interdisciplinary centre bringing together the unique strengths of Cambridge in medicine, biology, mathematics and the physical sciences. Read more
Introduced in 2004, this course was developed by the Cambridge Computational Biology Institute, an interdisciplinary centre bringing together the unique strengths of Cambridge in medicine, biology, mathematics and the physical sciences.

The course is aimed at introducing students to quantitative aspects of biological and medical sciences. It is intended for mathematicians, computer scientists and others wishing to learn about the subject in preparation for a PhD course or a career in industry. It is also suitable for students with a first degree in biosciences as long as they have strong quantitative skills (which should be documented in the application).

This 11-month course consists of core modules in bioinformatics, scientific programming with R, genomics, systems biology and network biology. Before the start of the first term, students are required to attend an introductory course in molecular biology. Courses are delivered in association with several University departments from the Schools of Biological Sciences and Physical Sciences, groups within the School of Clinical Medicine, the European Bioinformatics Institute and the Sanger Institute. The course concludes with a three-month internship in a university or industrial laboratory.

See the website http://www.graduate.study.cam.ac.uk/courses/directory/maammpcbi

Course detail

After completing the MPhil in Computational Biology, students will be expected to have:

- acquired a sound knowledge of a range of tools and methods in computational biology;
- developed the capacity for independent study and problem solving at a higher level;
- undertaken an internship project within a laboratory or group environment, and produced a project report;
- given at least one presentation on their project.

Format

The course combines taught lectures (October-April), followed by a summer internship project (May-August). There are typically 3-4 taught modules per term, and each module consists of 16 hours of lectures. Each module is assessed by coursework, and there is one general examination in May.

Placements

Students undertake a mandatory internship (May to August) in either a university or industrial laboratory. The Department will compile a list of possible opportunities which students can discuss directly with the host laboratory. Alternatively students may organise their own internship, subject to the approval of the Course Director.

Assessment

A 18,000 word (maximum) report must be written to summarise the student's internship. An oral presentation on this report must also be given.

Each module is assessed typically by two written assignments. These assignments involve significant computational elements.

A compulsory two-hour general examination is sat in May.

Continuing

MPhil students wishing to apply for a PhD at Cambridge must apply via the Graduate Admissions Office for continuation by the relevant deadline.

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

There are no specific funding opportunities advertised for this course. For information on more general funding opportunities, please follow the link below.

General Funding Opportunities http://www.graduate.study.cam.ac.uk/finance/funding

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