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Masters Degrees (Mathematical Medicine)

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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 MPhil in History and Philosophy of Science and Medicine is a full-time 9-month course that provides students with the opportunity to carry out focused research under close supervision by senior members of the University. Read more
The MPhil in History and Philosophy of Science and Medicine is a full-time 9-month course that provides students with the opportunity to carry out focused research under close supervision by senior members of the University. Students will acquire or develop skills and expertise relevant to their research interests, as well as a critical and well informed understanding of the roles of the sciences in society. Those intending to go on to doctoral work will learn the research skills needed to help them prepare a well planned and focused PhD proposal. During the course students gain experience of presenting their own work and discussing the issues that arise from it with an audience of their peers and senior members of the Department; they will attend lectures, supervisions and research seminars in a range of technical and specialist subjects central to research in the different areas of History and Philosophy of Science and Medicine.

The educational aims of the programme are:

- to give students with relevant training at first-degree level the opportunity to carry out focussed research in History, Philosophy of Science and Medicine under close supervision;
- to give students the opportunity to acquire or develop skills and expertise relevant to their research interests;
- to enable students to acquire a critical and well informed understanding of the roles of the sciences in society; and
- to help students intending to go on to doctoral work to acquire the requisite research skills and to prepare a well planned and focussed PhD proposal.

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

Course detail

The MPhil course is taught by supervisions and seminars and assessed by three research essays and a dissertation.

The topics of the essays and dissertation should each fall within the following specified subject areas:

1. General philosophy of science
2. History of ancient and medieval science, technology and medicine
3. History of early modern science, technology and medicine
4. History of modern science, technology and medicine
5. History, philosophy and sociology of the life sciences
6. History, philosophy and sociology of the physical and mathematical sciences
7. History, philosophy and sociology of the social and psychological sciences
8. History, philosophy and sociology of medicine
9. Ethics and politics of science
10. History and methodology of history, philosophy and sociology of science, technology and medicine

Format

The MPhil seminars are the core teaching resource for this course. In the first part of year these seminars are led by different senior members of the Department and focus on selected readings. During the rest of the year the seminars provide opportunities for MPhil students to present their own work.

Students are encouraged to attend the lectures, research seminars, workshops and reading groups that make the Department a hive of intellectual activity. The Department also offers graduate training workshops, which focus on key research, presentation, publication and employment skills.

The MPhil programme is administered by the MPhil Manager, who meets all new MPhil students as a group in early October, then sees each of the students individually to discuss their proposed essay and dissertation topics. The Manager is responsible for finding appropriate supervisors for each of these topics; the supervisors are then responsible for helping the student do the research and writing needed for the essays and the dissertation. Students will see each of their supervisors frequently; the MPhil Manager sees each student at regular intervals during the year to discuss progress and offer help and advice.

Supervisions are designed to provide students with the opportunity to set their own agenda for their studies. The supervisor's job is to support the student's research, not to grade their work – supervisors are formally excluded from the examination process.

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

Learning Outcomes

By the end of the course, students will have:

- Knowledge and Understanding -

- developed a deeper knowledge of their chosen areas of History, Philosophy of Science and Medicine and of the critical debates within them;
- acquired a conceptual understanding that enables the evaluation of current research and methodologies;
- formed a critical view of the roles of the sciences in society.

- Skills and other attributes -

By the end of the course students should have:

- acquired or consolidated historiographic, linguistic, technical and ancillary skills appropriate for research in their chosen area;
- demonstrated independent judgement, based on their own research;
- presented their own ideas in a public forum and learned to contribute constructively within an international environment.

Assessment

- A dissertation of up to 15,000 words. Examiners may request an oral examination but this is not normally required.
- Three essays, each of up to 5,000 words.

Students receive independent reports from two examiners on each of their three essays and the dissertation.

Continuing

The usual preconditions for continuing to the PhD are an overall first class mark in the MPhil, a satisfactory performance in an interview and agreement of the PhD proposal with a potential supervisor.

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

Funding Opportunities

- Rausing Studentships
- Raymond and Edith Williamson Studentships
- Lipton Studentships
- Wellcome Master's Awards

Please see the Department's graduate funding page for more information: http://www.hps.cam.ac.uk/studying/graduate/funding.html

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

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Oxford’s new MSc in Nanotechnology for Medicine and Health Care builds on the world-leading research in nanomedicine at the University’s Institute of Biomedical Engineering and other departments in the Mathematical, Physical and Life Sciences (MPLS) Division and Medical Sciences Division. Read more
Oxford’s new MSc in Nanotechnology for Medicine and Health Care builds on the world-leading research in nanomedicine at the University’s Institute of Biomedical Engineering and other departments in the Mathematical, Physical and Life Sciences (MPLS) Division and Medical Sciences Division. This advanced modular course is delivered by leading scientists and experts in this rapidly developing field and has been specifically designed for those who would value a part-time modular learning structure, for example those in full-time employment, both in the UK and overseas.

The MSc is designed to be completed part-time, normally over a two- to three-year period, and so provides a path to career development that is flexible and recognised within academia and industry. The programme comprises three online modules exploring the fundamentals of science and materials characterisation at the nanoscale, three intensive five-day face-to-face modules describing the clinical and commercial application of such science, and a piece of original lab-based research leading to the submission of a dissertation. This modular structure provides an adaptable approach to learning, and each module may also be taken as an individual short course.

There are opportunities to access and learn about cutting-edge research and current practice in a wide range of nanotechnology and healthcare topics from experts with experience of taking nanotechnologies from basic concept through clinical validation to market realisation. The tutor-led approach lends cohesion to the modular experience which is tailored for busy people in full-time employment who wish to minimise time away from the workplace to study.

Visit the website https://www.conted.ox.ac.uk/about/msc-in-nanotechnology-for-medicine-and-health-care

The first deadline for applications is Friday 20 January 2017

If your application is completed by this January deadline and you fulfil the eligibility criteria, you will be automatically considered for a graduate scholarship. For full details please see: http://www.ox.ac.uk/admissions/graduate/fees-and-funding/graduate-scholarships.

Description

Nanotechnology is the production and application of devices and systems at the nanometre scale, which is of the order of one billionth of a metre. Developments in this area of technology are now coming to fruition, and increasingly impacting on our daily lives. In particular, nanotechnology is becoming a crucial driving force behind innovation in medicine and healthcare, with a range of advances including nanoscale therapeutics, biosensors, implantable devices and imaging systems. However, the pace with which this revolution is occurring has left even some of its leading practitioners lacking in aspects of the key fundamental knowledge or the information required to navigate the regulatory and clinical pathway to achieve market realisation.

The University of Oxford's MSc in Nanotechnology for Medicine and Health Care offers a detailed and cutting-edge education in this subject and builds on the successful Postgraduate Certificate in Nanotechnology, which was launched in 2006. The course is taken part-time as a mixture of online and face-to-face modules, meaning it can fit around the demands of those working full-time and can be studied by international students without the requirement to relocate. The course uses a blend of individual study of learning materials, together with group work during live online tutorials, conventional lectures and discussions and also requires the student to submit a dissertation reporting an original piece of nanomedicine-based research. The group sessions with tutors are particularly valuable because they offer highly focused learning and assessment opportunities.

Programme details

The MSc in Nanotechnology for Medicine and Health Care is a part-time course consisting of six modules and a research project and associated dissertation. The programme is normally completed in two to three years. Students are full members of the University of Oxford and are matriculated as members of an Oxford college.

The modules in this programme can also be taken as individual short courses. It is possible to transfer credit from up to three previously completed modules into the MSc programme, if the time elapsed between commencement of the accredited module(s) and registration on the MSc is not more than two years.

The course comprises:

- three online modules giving a thorough introduction to the fundamental science of nanotechnology and the behaviour and characterisation of nanoscale materials;

- three five-day modules taught face-to-face in Oxford explaining the scientific, regulatory, clinical and commercial aspects of the application of nanotechnology to medicine and healthcare

- an original research project of approximately 18 weeks to be written up as a dissertation

The course has a dedicated Course Director, Associate Director and administration team accustomed to supporting students undertaking distance learning and face-to-face courses. Students have access to staff at the University of Oxford’s Begbroke Science Park and Institute of Biomedical Engineering, particularly the Course Director, Professor Robert Carlisle and the Associate Course Director, Dr Christiane Norenberg.

Throughout the course, students can use the University of Oxford’s excellent electronic library resources to enable them to complete the assignment tasks.

Programme modules:

- Module 1: The Wider Context of Nanotechnology (online)
- Module 2: The Fundamental Science of Nanotechnology (online)
- Module 3: Fundamental Characterisation for Nanotechnology (online with two-day component in Oxford)
- Module 4: Introduction to Bionanotechnology (in Oxford)
- Module 5: Nanomedicine – Science and Applications (in Oxford)
- Module 6: Clinical Translation and Commercialisation of Nanomedicine (in Oxford)

To complete the MSc, students need to attend the six modules and complete the assessed written assignments for each module, and complete a research project with dissertation on a topic chosen in consultation with a supervisor and the Course Director.

Who is it for?

This is a part-time, modular course leading to a postgraduate qualification at the University of Oxford. The course is designed for students wishing to study part-time. It will appeal to those working in the commercial, research or healthcare sectors who use or develop nanotechnology in their work. Applications are welcome from biomedical engineers, materials scientists, biotech-entrepreneurs, medical practitioners, chemists, pharmacists, electrical engineers, project managers in related industries, patent agents, legislators, as well as those involved in commercial or academic research in this area of science.

Find out how to apply here - http://www.ox.ac.uk/admissions/graduate/applying-to-oxford

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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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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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Joining the Department as a postgraduate is certainly a good move. The Department maintains strong research in both pure and applied mathematics, as well as the traditional core of a mathematics department. Read more
Joining the Department as a postgraduate is certainly a good move. The Department maintains strong research in both pure and applied mathematics, as well as the traditional core of a mathematics department. What makes our Department different is the equally strong research in fluid mechanics, scientific computation and statistics.

The quality of research at the postgraduate level is reflected in the scholarly achievements of faculty members, many of whom are recognized as leading authorities in their fields. Research programs often involve collaboration with scholars at an international level, especially in the European, North American and Chinese universities. Renowned academics also take part in the Department's regular colloquia and seminars. The faculty comprises several groups: Pure Mathematics, Applied Mathematics, Probability and Statistics.

Mathematics permeates almost every discipline of science and technology. We believe our comprehensive approach enables inspiring interaction among different faculty members and helps generate new mathematical tools to meet the scientific and technological challenges facing our fast-changing world.

The MPhil program seeks to strengthen students' general background in mathematics and mathematical sciences, and to expose students to the environment and scope of mathematical research. Submission and successful defense of a thesis based on original research are required.

Research Foci

Algebra and Number Theory
The theory of Lie groups, Lie algebras and their representations play an important role in many of the recent development in mathematics and in the interaction of mathematics with physics. Our research includes representation theory of reductive groups, Kac-Moody algebras, quantum groups, and conformal field theory. Number theory has a long and distinguished history, and the concepts and problems relating to the theory have been instrumental in the foundation of a large part of mathematics. Number theory has flourished in recent years, as made evident by the proof of Fermat's Last Theorem. Our research specializes in automorphic forms.

Analysis and Differential Equations
The analysis of real and complex functions plays a fundamental role in mathematics. This is a classical yet still vibrant subject that has a wide range of applications. Differential equations are used to describe many scientific, engineering and economic problems. The theoretical and numerical study of such equations is crucial in understanding and solving problems. Our research areas include complex analysis, exponential asymptotics, functional analysis, nonlinear equations and dynamical systems, and integrable systems.

Geometry and Topology
Geometry and topology provide an essential language describing all kinds of structures in Nature. The subject has been vastly enriched by close interaction with other mathematical fields and with fields of science such as physics, astronomy and mechanics. The result has led to great advances in the subject, as highlighted by the proof of the Poincaré conjecture. Active research areas in the Department include algebraic geometry, differential geometry, low-dimensional topology, equivariant topology, combinatorial topology, and geometrical structures in mathematical physics.

Numerical Analysis
The focus is on the development of advance algorithms and efficient computational schemes. Current research areas include: parallel algorithms, heterogeneous network computing, graph theory, image processing, computational fluid dynamics, singular problems, adaptive grid method, rarefied flow simulations.

Applied Sciences
The applications of mathematics to interdisciplinary science areas include: material science, multiscale modeling, mutliphase flows, evolutionary genetics, environmental science, numerical weather prediction, ocean and coastal modeling, astrophysics and space science.

Probability and Statistics
Statistics, the science of collecting, analyzing, interpreting, and presenting data, is an essential tool in a wide variety of academic disciplines as well as for business, government, medicine and industry. Our research is conducted in four categories. Time Series and Dependent Data: inference from nonstationarity, nonlinearity, long-memory behavior, and continuous time models. Resampling Methodology: block bootstrap, bootstrap for censored data, and Edgeworth and saddle point approximations. Stochastic Processes and Stochastic Analysis: filtering, diffusion and Markov processes, and stochastic approximation and control. Survival Analysis: survival function and errors in variables for general linear models. Probability current research includes limit theory.

Financial Mathematics
This is one of the fastest growing research fields in applied mathematics. International banking and financial firms around the globe are hiring science PhDs who can use advanced analytical and numerical techniques to price financial derivatives and manage portfolio risks. The trend has been accelerating in recent years on numerous fronts, driven both by substantial theoretical advances as well as by a practical need in the industry to develop effective methods to price and hedge increasingly complex financial instruments. Current research areas include pricing models for exotic options, the development of pricing algorithms for complex financial derivatives, credit derivatives, risk management, stochastic analysis of interest rates and related models.

Facilities

The Department enjoys a range of up-to-date facilities and equipment for teaching and research purposes. It has two computer laboratories and a Math Support Center equipped with 100 desktop computers for undergraduate and postgraduate students. The Department also provides an electronic homework system and a storage cloud system to enhance teaching and learning.

To assist computations that require a large amount of processing power in the research area of scientific computation, a High Performance Computing (HPC) laboratory equipped with more than 200 high-speed workstations and servers has been set up. With advanced parallel computing technologies, these powerful computers are capable of delivering 17.2 TFLOPS processing power to solve computationally intensive problems in our innovative research projects. Such equipment helps our faculty and postgraduate students to stay at the forefront of their fields. Research projects in areas such as astrophysics, computational fluid dynamics, financial mathematics, mathematical modeling and simulation in materials science, molecular simulation, numerical ocean modeling, numerical weather prediction and numerical methods for micromagnetics simulations all benefit from our powerful computing facilities.

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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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This programme is organised by Edinburgh Infectious Diseases (EID), which is hosted by the College of Medicine and Veterinary Medicine and the College of Science and Engineering. Read more

Research profile

This programme is organised by Edinburgh Infectious Diseases (EID), which is hosted by the College of Medicine and Veterinary Medicine and the College of Science and Engineering.

It provides an introduction to research methodology for biologists, medics and veterinarians. The training also provides an entry into PhD studies. Previous students have undertaken projects in the following areas:

antibiotic resistance and hospital-acquired infections
arthropod vector biology and vectorborne diseases
epidemiology and mathematical modelling of animal and human infections
functional genomics and bioinformatics
molecular diagnosis and point-of-care detection of infectious diseases
the immunology of bacterial and parasitic infections (including major tropical diseases such as malaria, lymphatic filariasis and river blindness)
the immunology of ruminant infections (for example Johne's Disease)
the pathogenesis of prion and viral diseases (animal and human, including herpes and HIV)

The learning process includes a one-year research project and during the study period students will be required to attend research seminars and lectures, including those on the related areas of immunology, microbiology and pathology. Training will also be given in generic skills including: statistics; project management and planning; oral and written presentational skills.

Depending on the project selected, students will learn how to apply modern molecular and biochemical techniques to the investigation of pathogenesis of infections, or the use of statistics and mathematical models to study the epidemiology of diseases.

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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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Mathematics is a core scientific subject and an essential basis for a range of other sciences. Read more
Mathematics is a core scientific subject and an essential basis for a range of other sciences. This programme brings together the latest developments in a range of mathematical disciplines to provide you with a thorough grounding in the subject, together with a substantial project that can be used to develop a specialisation.

Internationally leading research supports this programme, with particular research strengths including magnetic fields, interface of algebraic number theory and abstract algebra, climate system dynamics and display-structure on crystalline cohomology.
The programme prepares you for a career in numerous industries or for progression to a PhD for those interested in pursuing a research pathway.

Programme structure

The programme comprises three compulsory taught modules and 90 credits of option modules. The taught component of the programme is completed in June with the project extending over the summer period for submission in September.

Compulsory Modules

The compulsory modules can include; Research in Mathematical Sciences; Advanced Mathematics Project and Analysis and Computation for Finance

Optional Modules

Some examples of the optional modules are as follows;
Logic and Philosophy of Mathematics; Methods for Stochastics and Finance; Mathematical Theory of Option Pricing; Dynamical Systems and Chaos; Fluid Dynamics of Atmospheres and Oceans; Modelling the Weather and Climate; The Climate System; Algebraic Number Theory; Algebraic Curves; Waves, Instabilities and Turbulence; Magnetic Fields and Fluid Flows; Statistical Modelling in Space and Time and Mathematical Modelling in Biology and Medicine.

The modules we outline here provide examples of what you can expect to learn on this degree course based on recent academic teaching. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand.

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Infectious diseases remain a major contributor to the global burden of disease, with HIV, malaria, measles, diarrhoeal disease and respiratory infections responsible for over 50% of premature deaths worldwide. Read more
Infectious diseases remain a major contributor to the global burden of disease, with HIV, malaria, measles, diarrhoeal disease and respiratory infections responsible for over 50% of premature deaths worldwide. However the availability of resources for interventions is limited in comparison with the scale of the challenges faced. Over the last decade there has been increasing recognition of the value of epidemiological analysis and mathematical modelling in aiding the design and interpretation of clinical trials from a population perspective and, downstream, to guide implementation, monitoring and evaluation of intervention effectiveness. The Epidemiology, Evolution and Control of Infectious Diseases (EECID) stream provides a research-based training in infectious disease epidemiology, mathematical modelling and statistics, genetics and evolution, and computational methods. The focus of the course is inter-disciplinary, with a strong applied public health element.

Based in the Department of Infectious Disease Epidemiology in the Faculty of Medicine, the stream provides an opportunity to learn, in a supportive and stimulating environment, from leaders in the field who are actively engaged in research and advise leading public health professionals, policy-makers, governments, international organisations and pharmaceutical companies, both nationally and internationally, on a range of diseases include pandemic influenza, HIV, TB, malaria, polio and neglected tropical diseases (NTDs).

This stream is linked to the Wellcome Trust 4-year PhD programme in the Epidemiology, Evolution and Control of Infectious Diseases which includes up to 5 funded studentships each year. Up to 3 further 1+3 MRC studentships are also available each year.

The emphasis of the course will be to provide a thorough training in epidemiology, mathematical modelling and statistics, and genetics and evolution, as applied to infectious diseases. This research-orientated training will incorporate taught material, practical sessions in statistical software (R) and C programming as well as wider generic training in the research and communication skills needed to interact with public health agencies. Through the two research-based projects students will be exposed to the latest developments in the field and will gain first-hand experience in applying the methods they are taught to questions of public-health relevance.

Individuals who complete the course will have developed the ability to:

-Describe the biology, epidemiology and control of major global infectious diseases
-Interpret and present epidemiological data
-Undertake statistical analysis of infectious disease data including applying modern methods for statistical inference
-Develop and apply mathematical models to understand infectious disease dynamics, evolution and control
-Analyse genetic data using modern techniques and interpret their relevance to infectious disease epidemiology
-Critically evaluate research papers and reports
-Write and defend research reports and publications
-Communicate effectively through writing, oral presentations and IT to facilitate further study or employment in epidemiology and public health
-Exercise a range of transferable skills

This will be achieved through a course of lectures, seminars, tutorials and technical workshops. Please note that Postgraduate Diplomas and Certificates for part-completion are not available for this course.

The stream will be based in the Department of Infectious Disease Epidemiology on the St Mary’s campus of Imperial College London.

Each student chooses two projects over the course of the year from the wide range available. Students are guided in this choice by the stream organiser and their personal tutor and are advised to take contrasting projects to ensure a balanced training.

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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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The College of Liberal Arts and Sciences is a thriving center of intellectual excellence that encompasses 14 academic departments and 80 degree programs. Read more
The College of Liberal Arts and Sciences is a thriving center of intellectual excellence that encompasses 14 academic departments and 80 degree programs. Its more than 2,500 students are engaged in a wide variety of challenging courses and hands-on learning experiences that extend across all areas of the humanities and sciences – from the great philosophers and classic literature to the world economy and environmental sustainability.

At the core of each department are faculty members who have garnered national acclaim for their best-selling books, ground-breaking research and creative endeavors. Together, students and their professors explore globally significant subjects and work towards the goal of improving every aspect of the way in which human beings live. To learn more about a specific area of study, click on the left-hand navigation bar for a full listing of academic departments.

The department

The Department of Mathematics provides numerous undergraduate and graduate level courses that will enable you to master the mathematical methods and sophisticated reasoning and problem-solving skills essential to a wide variety of fields. In addition, the department offers a program to become an actuary.

The bachelor’s and master’s degree programs are designed to provide flexibility while emphasizing mathematical reasoning and problem solving, preparing the student for graduate school or a career in mathematics in secondary school teaching, business, industry, government or academia. In addition, a degree in mathematics is regarded as excellent preparation for entrance to professional schools of law, medicine or business.

M.S. in Mathematics for Secondary School Teachers

A high school teacher with an advanced knowledge of mathematics can make a profound impact on his or her students. A sophisticated understanding of mathematical concepts and problem-solving strategies can help bring high school-level math vividly to life for the adolescent student.

The M.S. in Mathematics for Secondary School Teachers is designed for people who are currently working as teachers or those who plan to enter the teaching field. This program makes the mathematics teacher more versatile and valuable to his or her school district.
The 37-credit Master of Science program consists of 25 credits of required courses covering such subjects as set theory, mathematical logic and information, abstract algebra, Euclidean geometry, history of mathematics and the foundations and applications of analysis. It also offers the opportunity to satisfy individual interests by requiring 12 credits of electives. As a capstone project, students either write a thesis or prepare a lecture on mathematics suitable for high school students.

Note: This program does not lead to New York State teaching certification

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This one-year, research-led course will fully prepare you for a career within an exciting and ever-expanding field. Read more
This one-year, research-led course will fully prepare you for a career within an exciting and ever-expanding field. You’ll develop expertise in systems analysis and mathematical modelling for application to processes in biomedicine; compartmental modelling in physiology and medicine; physical principles in medicine; properties and design of the materials employed in medical applications; and signal processing and data analysis techniques for physiological data.

Our supportive teaching staff will encourage you to generate new and forward-thinking ideas as part of your independent research project. Projects initiated by former students include: Bone Investigation using Infrared Detection; Modelling Gas Exchange in the Human Respiratory System and Modelling of Acute Hypercalcemia Immunotherapy Treatment. Recent graduates have progressed into careers that range from biomedical engineering and biotechnology to pharmaceutical industries and research.

Core modules

-Fundamentals of Biomedical Engineering
-Imaging and Sensing in Body and Brain
-Biomechanics
-Biomedical Systems Modelling
-Biomedical Signal Processing

Optional modules

Choose one from the following:
-Biomedical Materials, Tissue Engineering and Regenerative Medicine
-Healthcare Technology Engineering: Design, Maintenance and Assessment

Individual project

Half the course credit comprises a substantial project appropriate to the course of study. This entails an in-depth experimental, theoretical or computational investigation of a topic chosen by the student in conjunction with an academic supervisor.

The modules are delivered thoughout the first two terms. The module cycle is typically 3 or more more lectures per week plus seminars and laboratory exercises. Where possible the modules are interleaved in pairs. Each module has a coursework exercise associated with it to be completed within 1 month of the end of the module to demonstrate the student's understanding of the subject.

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