Process and Environmental Systems Engineering

Study mode:On campus Study type:Full-time Languages: English
Local:$ 8.17 k / Year(s) Foreign:$ 23.8 k / Year(s)  
StudyQA ranking:4374 Duration:12 months

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This programme provides a strong theoretical foundation and hands-on experience of the experimental technologies and computational skills required for truly integrative systems biology research.

Why Surrey?
Our programme aims to produce interdisciplinary scientists capable of working in the field of systems biology, such that they are able to design system-level experiments, acquire and interpret large-scale data, run system-level simulations and draw conclusions.

By generating and analysing your own data, you will gain first-hand experience of the skills and techniques needed to understand an organism at a systems level, from beginning to end, in an experimental setting.

Programme overview
There is great demand for interdisciplinary scientists who are capable of generating, handling, analysing and interpreting the high-throughput data obtained from current biological research in academia and industry. Being able to effectively contribute and communicate within a skills-diverse research team will soon be considered an essential employee skill.

This full-time programme is especially useful for:

* Graduates from the physical, mathematical / computational sciences wishing to apply their skills to biological research
* Graduates from the biological sciences wishing to enhance their mathematical/computational skills

The modular nature of the programme allows a flexible rate of attendance (one to four modules per year) and is suitable for candidates with additional work commitments wishing to learn new skills within a Continuing Professional Development framework.

The programme consists of eight 3.5-week modules, totalling 120 credits (15 credits each), and a twelve-week research project worth 60 credits.

The MSc requires 180 credits, the Postgraduate Diploma requires 120 credits and the Postgraduate Certificate requires 60 credits.

The full-time Masters programme is designed to be completed within one academic year. You may register for the Postgraduate Certificate, Postgraduate Diploma or MSc at any time, provided that no more than four modules have been completed and the required number of credits can be achieved within the current academic year.

Each of the 3.5-week modules can be taken as a stand-alone course and/or as part of professional development. Please enquire for details of the timing of each module.

Module overview

Complementary Foundation Course
This preparatory module is designed to provide complementary knowledge to your own original discipline, enabling you to commence systems biology research.

For biologists, this module provides an introduction to basic mathematics and programming techniques relevant to systems biology.

For engineering/mathematics/physical scientists, this module provides an introduction to biomedical science, including a one-week intensive course in basic laboratory skills relevant to the systems biology field.

Theory behind experimental methods in quantitative biology
This module provides comprehensive knowledge of the theoretical concepts of experimental techniques used to capture global measurements for the cell/organism. The underlying molecular mechanisms within the cell and the laboratory techniques related to Phenomics, Genomics, Transcriptomics, Proteomics, Metabolomics and Synthetic Biology will be covered.

Practical experience in experimental methods in quantitative biology
This module provides hands-on experience of generating large-scale data following a systems biology experimental approach using high-throughput -omics techniques.

Computing skills for Systems Biology
This module is designed to give supported, hands-on experience of computational programming with the interpreted languages Perl/Python and data analysis within the programming environment R. Key data retrieval and data manipulation skills required for Systems Biology research will be covered. All students will be exposed to the interpreted languages of Perl and Python but it is the choice of the student which language they adopt (through personal preference/career path, as discussed in the module). Skills established within this module will be further developed in subsequent modules.

Good practice in Systems Biology research
This module exposes students to current research within the field. It is designed to provide the necessary conceptual understanding of how the methods covered in previous modules, and to be covered in subsequent modules, can be combined to design and conduct a successful Systems Biology research project.

The skills developed in this module will directly support students in completing their work/research in subsequent modules.

Bioinformatics analysis underpinning Systems Biology
This module provides conceptual understanding and hands-on experience of Bioinformatic approaches for analysing and interpreting high-throughput -omics data using a combination of online tools, in-house scripts and data analysis packages within the programming environment R. The techniques learnt in Computing skills for Systems Biology will be further developed in this module.

Computational Systems Biology
This module provides comprehensive knowledge of the main current techniques used in computational systems biology: constraint-based modelling of genome-scale metabolic networks; computer simulation of ordinary differential equation models; exact stochastic simulation of molecular interaction networks; hybrid computer simulation of multiscale models; Petri Net representation of molecular interaction networks and model checking.

Mathematical modelling
This module provides comprehensive knowledge of mathematical modelling techniques to model and analyse molecular networks. Topics covered: timescale analysis in (systems of) deterministic ODEs (metabolic and gene expression case studies); introduction to dynamical systems theory (steady states, linear stability analysis, bifurcations); multistability and oscillations; stochasticity in molecular biology; intrinsic and extrinsic noise; Langevin equations and master equations; stochastic gene expression.

At least a 2.2 degree (or equivalent) in a relevant discipline (biology, mathematics, engineering, physics and/or computational science).Applicants not possessing the qualifications mentioned above may be considered, depending on the length and quality of their practical experience and recommendations from employers/supervisors. The first module of the full-time MSc course provides complementary knowledge to your own original discipline. Students who consider themselves to have a biology-based background should have biological knowledge equivalent to that obtained from a bachelors degree and skills relevant to working within a laboratory. Students who consider themselves to have an engineering/maths/physical science-based background should have mathematical knowledge equivalent to that obtained from a bachelors degree and computational skills suitable for basic programming.Selection is based upon the candidates application and references. An informal interview may be required.English language requirementsIELTS min overall 7.0IELTS min by component 6.5We offer intensive English language pre-sessional courses, designed to take you to the level of English ability and skill required for your studies here. English Language Requirements IELTS band: 7 IMPORTANT NOTE: Since April 2014 the ETS tests (including TOEFL and TOEIC) are no longer accepted for Tier 4 visa applications to the United Kingdom. The university might still accept these tests to admit you to the university, but if you require a Tier 4 visa to enter the UK and begin your degree programme, these tests will not be sufficient to obtain your Visa. The IELTS test is most widely accepted by universities and is also accepted for Tier 4 visas to the UK- learn more.
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