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Masters Degrees (Mathematical Medicine And Biology)

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The MSc Mathematical Medicine and Biology will provide you with skills suitable for a research career in the exciting and growing field of mathematical medicine and biology. Read more

Overview

The MSc Mathematical Medicine and Biology will provide you with skills suitable for a research career in the exciting and growing field of mathematical medicine and biology.

You will take core modules in biology and the application of mathematics to medicine and biology. More advanced modules will introduce research topics in biomedical mathematics, including options in Computational Biology and Theoretical Neuroscience.

The taught training programme will be followed by a substantial individual project leading to a dissertation.

Throughout the course, the exceptional strength of the Centre for Mathematical Medicine and Biology will facilitate your hands-on experience of interdisciplinary biomedical research.

Some teaching activities will take place at the Sutton Bonington campus. The University provides a regular free hopper bus between University Park and Sutton Bonington.

Key facts:

- This course is informed by the work being carried out in the Centre for Mathematical Medicine and Biology.

- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 50 full-time academic staff.

- In the latest independent Research Assessment Exercise, the school ranked eighth in the UK in terms of research power across the three subject areas within the School of Mathematical Sciences (pure mathematics, applied mathematics, statistics and operational research).

Module details

Biomolecular Data and Networks

Cell Structure and Function for Engineers

Computational and Systems Biology

Mathematical Medicine and Biology

Mathematical Medicine and Biology Dissertation

Practical Biomedical Modelling

Theoretical Neuroscience

Topics in Biomedical Mathematics

English language requirements for international students

IELTS: 6.0 (with no less than 5.5 in any element)

Further information



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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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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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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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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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he contribution of mathematical and computational modelling to the understanding of biological systems has rapidly grown in recent years. Read more
he contribution of mathematical and computational modelling to the understanding of biological systems has rapidly grown in recent years. This discipline encompasses a wide range of life science areas, including ecology (e.g. population dynamics), epidemiology (e.g. spread of diseases), medicine (e.g. modelling cancer growth and treatment) and developmental biology.

This programme aims to equip students with the necessary technical skills to develop, analyse and interpret models applied to biological systems. Course work is supported by an extended and supervised project in life science modelling.

Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer. A typical distribution for this programme is as follows:

Core courses

Modelling and Tools;
Mathematical Ecology;
Dynamical Systems;
Mathematical Biology and Medicine.

Optional Courses

Optimization;
Numerical Analysis of ODEs;
Applied Mathematics;
Statistical Methods;
Stochastic Simulation;
Partial Differential Equations;
Numerical Analysis;
Geometry;
Climate Change: Causes and Impacts;
Biologically Inspired Computation;
Climate Change: Mitigation and Adaptation Measures.

Typical project subjects

Population Cycles of Forest Insects;
Modelling Invasive Tumour Growth;
The replacement of Red Squirrels by Grey Squirrels in the UK;
Wiring of Nervous System;
Vegetation Patterning in Semi-arid Environments;
Daisyworld: A Simple Land Surface Climate Model.

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Climate change is recognised as having potentially huge impacts on the environment and on human society. Read more
Climate change is recognised as having potentially huge impacts on the environment and on human society. This programme aims to provide an understanding of climate change causes, impacts, mitigation and adaptation measures from a life science perspective in conjunction with developing a wide variety of mathematical modelling skills that can be used to investigate the impacts of climate change.

The programme closely follows the structure of our Applied Mathematical Sciences MSc. Two of the mandatory courses will specifically focus on understanding the issues related to climate change and are taught by the School of Life Sciences.

Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer. A typical distribution for this programme is as follows:

Core courses

Modelling and Tools;
Mathematical Ecology;
Climate Change: Causes and Impacts;
Climate Change: Mitigation and Adaptation Measures;
Dynamical Systems (recommended);
Stochastic Simulation (recommended)

Optional Courses

Optimization;
Mathematical Biology and Medicine;
Numerical Analysis of ODEs;
Applied Mathematics;
Statistical Methods;
Applied Linear Algebra;
Partial Differential Equations;
Numerical Analysis;
Geometry;
Bayesian Inference.

Typical project subjects

Population Cycles of Forest Insects;
Climate Change Impact;
The replacement of Red Squirrels by Grey Squirrels in the UK;
Vegetation Patterns in Semi-arid Environments;
Daisyworld: A Simple Land Surface Climate Model.

The final part of the MSc is an extended project in mathematical modelling the impacts of climate change on environmental systems, giving the opportunity to investigate a topic in some depth guided by leading research academics.

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Applied Mathematical Sciences offers a clear and relevant gateway into a successful career in business, education or scientific research. Read more
Applied Mathematical Sciences offers a clear and relevant gateway into a successful career in business, education or scientific research. The programme arms students with the essential knowledge required by all professional mathematicians working across many disciplines. You will learn to communicate their ideas effectively to peers and others, as well as the importance of research, planning and self-motivation.

Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer. A typical distribution for this programme is as follows:

Core courses

:

Modelling and Tools;
Optimization;
Dynamical Systems;
Applied Mathematics (recommended);
Applied Linear Algebra (recommended).

Optional Courses

:

Mathematical Ecology;
Functional Analysis;
Numerical Analysis of ODEs;
Pure Mathematics;
Statistical Methods;
Stochastic Simulation;
Software Engineering Foundations;
Mathematical Biology and Medicine;
Partial Differential Equations;
Numerical Analysis;
Geometry.

Typical project subjects

:

Pattern Formation of Whole Ecosystems;
Climate Change Impact;
Modelling Invasive Tumour Growth;
Simulation of Granular Flow and Growing Sandpiles;
Finite Element Discretisation of ODEs and PDEs;
Domain Decomposition;
Mathematical Modelling of Crime;
The Geometry of Point Particles;
Can we Trust Eigenvalues on a Computer?

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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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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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Research in the Division of Genetics and Genomics aims to advance understanding of complex animal systems and the development of improved predictive models… Read more

Research profile

Research in the Division of Genetics and Genomics aims to advance understanding of complex animal systems and the development of improved predictive models through the application of numerical and computational approaches in the analysis, interpretation, modelling and prediction of complex animal systems from the level of the DNA and other molecules, through cellular and gene networks, tissues and organs to whole organisms and interacting populations of organisms.

The biology and traits of interest include: growth and development, body composition, feed efficiency, reproductive performance, responses to infectious disease and inherited diseases.

Research encompasses basic research in bioscience and mathematical biology and strategic research to address grand challenges, e.g. food security.

Research is focussed on, but not restricted to, target species of agricultural importance including cattle, pigs, poultry, sheep; farmed fish such as salmon; and companion animals. The availability of genome sequences and the associated genomics toolkits enable genetics research in these species.

Expertise includes genetics (molecular, quantitative), physiology (neuroendocrinology, immunology), ‘omics (genomics, functional genomics) with particular strengths in mathematical biology (quantitative genetics, epidemiology, bioinformatics, modelling).

The Division has 18 Group Leaders and 4 career track fellows who supervise over 30 postgraduate students.

Training and support

Studentships are of 3 or 4 years duration and students will be expected to complete a novel piece of research which will advance our understanding of the field. To help them in this goal, students will be assigned a principal and assistant supervisor, both of whom will be active scientists at the Institute. Student progress is monitored in accordance with School Postgraduate (PG) regulations by a PhD thesis committee (which includes an independent external assessor and chair). There is also dedicated secretarial support to assist these committees and the students with regard to University and Institute matters.

All student matters are overseen by the Schools PG studies committee. The Roslin Institute also has a local PG committee and will provide advice and support to students when requested. An active staff:student liaison committee and a social committee, which is headed by our postgraduate liaison officer, provide additional support.

Students are expected to attend a number of generic training courses offered by the Transkills Programme of the University and to participate in regular seminars and laboratory progress meetings. All students will also be expected to present their data at national and international meetings throughout their period of study.

Facilities

In 2011 The Roslin Institute moved to a new state-of-the-art building on the University of Edinburgh's veterinary campus at Easter Bush. Our facilities include: rodent, bird and livestock animal units and associated lab areas; comprehensive bioinformatic and genomic capability; a range of bioimaging facilities; extensive molecular biology and cell biology labs; café and auditorium where we regularly host workshops and invited speakers.

The University's genomics facility Edinburgh Genomics is closely associated with the Division of Genetics and Genomics and provides access to the latest genomics technologies, including next-generation sequencing, SNP genotyping and microarray platforms (genomics.ed.ac.uk).

In addition to the Edinburgh Compute and Data Facility’s high performance computing resources, The Roslin Institute has two compute farms, including one with 256 GB of RAM, which enable the analysis of complex ‘omics data sets.

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Accurate and efficient scientific computations lie at the heart of most cross-discipline collaborations. It is key that such computations are performed in a stable, efficient manner and that the numerics converge to the true solutions, dynamics of the physics, chemistry or biology in the problem. Read more
Accurate and efficient scientific computations lie at the heart of most cross-discipline collaborations. It is key that such computations are performed in a stable, efficient manner and that the numerics converge to the true solutions, dynamics of the physics, chemistry or biology in the problem.

The programme closely follows the structure of our Applied Mathematical Sciences MSc and will equip you with the skill to perform efficient accurate computer simulations in a wide variety of applied mathematics, physics, chemical and industrial problems.

Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer. A typical distribution for this programme is as follows:

Core courses

Modelling and Tools;
Stochastic Simulation;
Applied Linear Algebra;
Numerical Analysis;

Optional Courses

Dynamical Systems;
Optimization;
Partial Differential Equations;
Numerical Analysis of ODEs;
Applied Mathematics;
Statistical Methods;
Functional Analysis;
Software Engineering Foundations;
Mathematical Biology and Medicine;
Biologically Inspired Computation;
Advanced Software Engineering;
Geometry;
Bayesian Inference;

Typical project subjects

Simulation of Granular Flow and Growing Sandpiles;
Finite Element Discretisation of ODEs and PDEs;
Domain Decomposition;
Computational Spectral Theory;
Mathematical Modelling of Crime;
Mathematical Modelling of Micro-electron Mechanical Systems.
Can we Trust Eigenvalues on a Computer?

The final part of the MSc is an extended project in computational mathematics, giving the opportunity to investigate a topic in some depth guided by leading research academics from our 5-rated mathematics and statistics groups.

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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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The Modelling Biological Complexity MRes is designed for students who wish to develop the skills to apply mathematical, computational and physical science techniques to real biological problems. Read more
The Modelling Biological Complexity MRes is designed for students who wish to develop the skills to apply mathematical, computational and physical science techniques to real biological problems. The programme provides a broad overview of the cutting edge research at the interface of the life, mathematical and physical sciences.

Degree information

Foundation courses use innovative teaching methods for interdisciplinary research to provide essential background knowledge in mathematical, computational and physical techniques and a broad introduction to core biological concepts and systems. A range of interdisciplinary research-driven projects follow in which students gain experience of different research techniques and a range of areas of biological interest.

Students undertake modules to the value of 180 credits.

The programme consists of four compulsory modules: foundation courses module, transferable skills module (20%), three mini projects (40%) and a research (summer) project (40%). There are no optional modules for this programme.

Core modules
-Modelling Biological Complexity: Foundation Course (non credit bearing)
-Transferable and Generic Skills
-Mini projects
-Research (summer) Project

Dissertation/report
All students undertake an independent research (summer) project, which culminates in a dissertation of up to 15,000 words, a short presentation and an oral examination.

Teaching and learning
The programme is delivered through a combination of lectures, laboratory work, case presentations, seminars, tutorials and project work. Student performance is assessed by essays, mini projects, oral and poster presentations, a computer programming and biological database task, web development, the research project and an end-of-year viva.

Careers

After passing the MRes, students may have the opportunity to progress onto a PhD at UCL.

Employability
CoMPLEX has built upon relationships with partners within academia and industry, to develop our existing CoMPLEX programme. so that it continues to be designed specifically to provide training that meets market needs. Graduates have excellent publication outputs, this, together with CoMPLEX's international reputation means that graduates are and will continue to be recognised when entering the job market. 70% of recent graduates have taken up positions in research centres in the UK and abroad. As small number have pursued careers in science policy analysis, cyber security, science teaching, statistical and mathematical consultancy, technology consultancy, or in management and the financial sector.

Why study this degree at UCL?

CoMPLEX is UCL's centre for interdisciplinary research in the life sciences. It brings together life and medical scientists with computer scientists, mathematicians, physicists and engineers to tackle the challenges arising from complexity in biology and medicine.

CoMPLEX collaborates with 250+ supervisors from 40 UCL Departments and maintains strong links with leading UK/International research institutions, charities and industrial partners e.g. AstraZeneca, British Heart Foundation, CRUK, Francis Crick Institute, GlaxoSmithKline, Microsoft Research and Renishaw. As a result CoMPLEX students have a vast range of projects to choose from and the opportunity to network with a plethora of scientific partners.

Peer-to-peer learning is a crucial part of the training, and students will take part in cohort activities, such as, mentoring events, a seminar series, outreach groups and an annual retreat.

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In recent years, biological research has become increasingly interdisciplinary, focusing heavily on mathematical modeling and on the analysis of system-wide quantitative information. Read more

Computational Life Science

In recent years, biological research has become increasingly interdisciplinary, focusing heavily on mathematical modeling and on the analysis of system-wide quantitative information. Sophisticated high-throughput techniques pose new challenges for data integration and data interpretation. The Computational Life Science (CompLife) MSc program at Jacobs University meets these challenges by covering computational, theoretical and mathematical approaches in biology and the life sciences. It is geared towards students of bioinformatics, computer science, physics, mathematics and related areas.

Program Features

The CompLife program is located at Jacobs University, a private and international English-language academic institution in Bremen, Germany. CompLife students at Jacobs University take a tailor-made curriculum comprising lectures, seminars and laboratory trainings. Courses cover foundational as well as advanced topics and methods. Core components of the program and areas of specialization include:

- Computational Systems Biology
- Computational Physics and Biophysics
- Bioinformatics
- RNA Biology
- Imaging and Modeling in Medicine
- Ecological Modeling
- Theoretical Biology
- Applied Mathematics
- Numerical Methods

For more details on the CompLife curriculum, please visit the program website at http://www.jacobs-university.de/complife.

Career Options

Graduates of the CompLife program are prepared for a career in biotechnology and biomedicine. Likewise, graduates of the program are qualified to move on to a PhD.

Application and Admission

The CompLife program starts in the first week of September every year. Please visit http://www.jacobs-university.de/graduate-admission or use the contact form to request details on how to apply. We are looking forward to receiving your inquiry.

Scholarships and Funding Options

All applicants are automatically considered for merit-based scholarships of up to € 12,000 per year. Depending on availability, additional scholarships sponsored by external partners are offered to highly gifted students. Moreover, each admitted candidate may request an individual financial package offer with attractive funding options. Please visit http://www.jacobs-university.de/study/graduate/fees-finances to learn more.

Campus Life and Accommodation

Jacobs University’s green and tree-shaded campus provides much more than buildings for teaching and research. It is home to an intercultural community which is unprecedented in Europe. A Student Activities Center, various sports facilities, a music studio, a student-run café/bar, concert venues and our Interfaith House ensure that you will always have something interesting to do.

For graduate students who would like to live on campus, Jacobs University offers accommodation in four residential colleges. Each college has its own dining room, recreational lounge, study areas, and common and group meeting rooms. Please visit http://www.jacobs-university.de/study/graduate/campus-life for more information.

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