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Aquatic ecosystems and species are under intense anthropogenic threats. These threats directly affect services such as sustainable fisheries, drinking water or ecosystem resilience. Read more

Aquatic ecosystems and species are under intense anthropogenic threats. These threats directly affect services such as sustainable fisheries, drinking water or ecosystem resilience. To adequately respond to these 21st century challenges and conserve these goods and services, a fundamental understanding of the biodiversity and ecosystem processes is needed, as without knowledge there can be no application or effective management.

Considering both freshwater and marine ecosystems and species, we have designed a programme to equip you with the interdisciplinary practical skills and theoretical understanding to pursue a career in aquatic research, consultancy or environmental protection, and give you a good understanding of applying scientific understanding to science policy. 

This programme balances the latest in ecological theory, conservation biology and evolutionary biology with practical application. You will take part in three residential field-courses (Dorset, Cumbria and Cape Verde) for practical, hands-on training.

You will be supervised by research-active scientists, becoming part of their research groups. We support links with a range of NGOs or potential employer organisations and strongly encourage you to publish your project work.

Programme highlights

  • Balances the latest in ecological theory with practical application
  • Residential field courses for practical, hands-on training in the field
  • Access to analytical, mesocosm and temperature-controlled facilities within the Centre for the Aquatic and Terrestrial Environment
  • Strong foundation for employment with environmental protection and conservation agencies, the water industry and environmental consultancies or PhD research 

Research and teaching 

You will have access to analytical research facilities within our Centre for the Aquatic and Terrestrial Environment, developed from an investment of £1.8 million in analytical equipment and specialist laboratory facilities. You will also have access to the Freshwater Biological Association’s River Laboratory on the River Frome in Dorset, via our River Communities Group, and to mesocosm and temperature controlled facilities at QMUL. Furthermore you can make use of our network of partner NGOs, research labs and industries to create further opportunities.

By choosing to study at a Russell Group university, you will have access to excellent teaching and top-class research. You can find out more about our research interests and view recent publications on the School of Biological and Chemical Science's Aquatic Ecology Research group page.

Centre for the Aquatic and Terrestrial Environment (CATE)

(CATE) at Queen Mary is an interdisciplinary collaboration between the School of Biological and Chemical Sciences and the School of Geography.

CATE builds on existing research strengths in areas of environmental research such as biogeochemistry, freshwater and marine ecology, terrestrial ecology and conservation. These facilities are used either in the formal teaching of this programme or are available for individual research projects.

Dorset Field Facilities

The Aquatic Ecology Group has a complementary unit (the River Communities Group) who do applied research, based at the River Laboratory of the Freshwater Biological Association in Dorset. We have a suite of ponds, 50% of which are heated above ambient temperatures, in which run long-term climate change experimentation. You will have the opportunity to conduct both field work and lab projects at this site.

Structure

  • Ecosystem Structure and Function: Ecosystems are under continued and growing threat from human activity (e.g. habitat loss, invasive species and diffuse pollution) and if we seek to preserve them then we need to understand how ecosystems function and how they respond to either enforced or natural change. Here we focus on the structural and functional elements of many ecosystems, from shallow lakes to tropical forests, with a particular focus on contrasting aquatic environments.
  • Statistics and Bioinformatics: Covers core statistics methods, within the R statistical computing environment. R has become the de facto environment for downstream data analysis and visualisation in biology, thanks to the hundreds of freely available R packages that allow biological data analysis solutions to be created quickly and reliably.
  • Quantitative Techniques for Surveying and Monitoring in Ecology: In the first week, there will be a series of lectures, workshops and practical data analyses classes where you will learn the theory behind designing and initiating surveys and monitoring campaigns for research projects and also for conservation & management. In the subsequent week, you will be able to put the theory into practice in the field at a location such as Lake Windermere and environs: here you will undertake electrofishing and hydroacoustic surveys for fish populations, zooplankton and benthic invertebrate surveys, a census for aquatic birds, and camera-trapping for aquatic mammals. Other skills such as the use of the modern telemetric tools will be demonstrated.
  • Science into Policy and Management – includes week in Dorset: Here a broad spectrum of human environmental impacts and their mitigation will be explored. The first half of the module will bring the student ‘face to face’ with potential regulators, practitioners and potential employers (typically Defra, Environment Agency, Natural England) through a series of guest lectures. These topics are then explored and summarised through an unpacking and feedback workshop. The second half is field based with current practitioners working directly in the field of bioassessment and biomonitoring. National and international legislation and directives are introduced through a series of case studies to look at the link between successful science and policy.
  • Marine Mammals and Turtles – field course to Cape Verde: The module focuses on the diversity, behaviour, ecology, physiology, conservation and management of cetaceans (whales and dolphins), and marine turtles. It covers such issues as the life history and migrations of turtles, their diving ability and behaviours, the social behaviour of dolphins, and the conservation of whales. It also includes (even though they are not mammals or reptiles!) a brief look at the sea-birds and sharks that will likely also be seen during field excursions. For part of the module you will be taught in the archipelago of Cape Verde, with boat trips for whales and shark observations, sea turtle monitoring. Mornings will be dedicated to lectures and workshops while afternoons and evening will be dedicated to hands-on practical experience.
  • Tropical Ecology and Conservation – field course, usually to either Borneo or Cape Verde


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The world is awash with data and much more is on the way, creating a tidal wave of Big Data. Data Engineers develop the infrastructure to store, manage, analyse this wave of data, to bridge the gap between Data and Computer Science. Read more
The world is awash with data and much more is on the way, creating a tidal wave of Big Data. Data Engineers develop the infrastructure to store, manage, analyse this wave of data, to bridge the gap between Data and Computer Science. This unique course will give you the skills you’ll need to succeed as a Data Engineer.

Why study Data Engineering at Dundee?

The role of “Data Scientist” has been described as the “sexiest job of the 21st Century. However, there is a emerging a new role, that of Data Engineer as more companies are realising they need employees with specific skills to handle the amount of data that is being generated and the coming tidal wave from the Internet of Things.

This MSc has been created with industry input to prepare its students with the skills to handle this wave of data and to be at the forefront of its exploitation. Students on the sister programmes (“Data Science” and “Business Intelligence”) have gone on to work for some of the biggest companies in the industry and we are confident that graduates from this MSc will have the same success.

The School of Computing at the University of Dundee has been successfully offering related MSc programmes such as Business Intelligence and Data Science since 2010. These innovative programmes attract around 40 students per year, drawn from across Europe and Overseas.

What's so good about Data Engineering at Dundee?

Our facilities:
You will have 24-hour access to our award winning and purpose-built Queen Mother Building. It has an unusual mixture of lab space and breakout areas, with a range of conventional and special equipment for you to use. It's also easy to work on your own laptop as there is wireless access throughout the building. Our close ties to industry allows us access to facilities such as Windows Azure and Teradata, and university and industry standard software such as Tableau for you to evaluate and use.

Special features

The University of Dundee has close ties with the Big Data industry, including Teradata, Datastax and Microsoft. We have worked with SAS, Outplay, Tag, GFI Max, BrightSolid and BIPB, and our students have enjoyed guest lectures from Big Data users such as O2, Sainsbury’s, M&S and IBM.

You will be able to work with a range of leading researchers and tutors, including top vision and imaging researchers and BI experts. Our honorary staff include legal experts, entrepreneurs and renowned industry experts such as John Richards of the newly formed IBM Watson Group.

How you will be taught

The course will be taught by staff of the School of Computing. Depending on the modules you take this will include Andy Cobley, Professor Mark Whitehorn, and Professor Stephen McKenna.

What you will study

The course will be taught in 20 credit modules with a 60 credit dissertation. Students will require to complete 180 credits for the award of the MSc (including 60 credits for the dissertation). Students completing 120 credits (without the dissertation) will be eligible for a Postgraduate Diploma.

Course content

Each module on the course is designed to give the student the skills and understanding they need to succeed in the Data Engineering/ Science field. Content on the course includes (but is not limited to):

CAP theorem
Lamda Architecture
Cassandra, Neo4j and other nosql databases
The Storm distributed real time computation system
Hadoop, HDFS, MapReduce, and other Hadoop/SQL technologies
Spark and Shark frameworks
Data Engineering languages such as Python, erlang, R, Matlab
Vision systems, which are becoming increasingly important in data engineering for extracting features from large quantities of images such as from traffic, medical and industrial
RDBMS systems which will continue to play an important role in data handing and storage. You will be expected to research the history of RDMBS and delve in to the internals of modern systems
OLAP cubes and Business Intelligence systems, which can be the best and quickest way to extract information from data stores
Goals of machine learning and data mining
Clustering: K-means, mixture models, hierarchical
Dimensionality reduction and visualisation
Inference: Bayes, MCMC
Perceptrons, logistic regression, neural networks
Max-margin methods (SVMs)
Mining association rules
Bayesian networks

How you will be assessed

The course is assessed through a combination of examinations, coursework, presentations and interviews. Each module is different: for instance the Big data module has 40% coursework, consisting of Erlang programming and a presentation on nosql databases, along with an examination worth 60%.

Careers

Our experience suggests that graduates of this course will have most impact in the following areas:

Cloud and web based industries that handle large volumes of fast moving data that need to be stored, analysed and maintained. Examples include the publishing industry (paper, TV and internet), messaging services, data aggregators and advertising services

Internet of Things. A large amount of data is being generated by devices (robotic assembly lines, home power management, sensors etc.) all of which needs to be stored and analysed.

Health. The NHS (and others) are starting to store and analyse patient data on an unprecedented scale. The healthcare industry is also combining data sources from a large number of databases to improve patient well-being and health outcomes

Games industry. The games industry records an extraordinary amount of data about its customers' play activities, all of which needs to be stored and analysed. This course will equip students with the knowledge and skill to engage with the industry.

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