Curating Science will enable you to develop an independent academic and curatorial practice at the intersection of histories, philosophies and social studies of science, science communication and museum studies.
You will engage with current debates in science communication and interpretive practice in museums, including cutting-edge art-science practices that are reimagining ways of knowing and being in the 21st Century. Alongside this, you will be encouraged to develop innovative practices of dialogic and participative engagement, developing their own ways of convening public spaces for debate.
You will undertake a range of active learning activities from developing displays, programmes and events to developing digital content and designing their own research projects. You will be supported throughout by an interdisciplinary academic staff team drawn from museum and curatorial studies and the histories and philosophies of science, as well as professionals from our partner institutions.
Students can specialise in their own areas of interest, through choosing from an array of optional modules that explore contemporary curatorial strategies, technologies and media, cultural memory, histories of medicine, audiences, participation and engagement. You will have the option of undertaking a negotiated placement with a museum or heritage organisation.
All students on the MA in Curating Science will take three core modules.
The History and Theory of Modern Science Communication allows students to explore how science, technology and medicine have been communicated to a wider public in the past. Students will identify how the processes and purposes of science communication has changed over the last two centuries and debate the consequences for science communication of the introduction of new media, ranging from the radio to the internet. The module addresses these questions by surveying the development of science communication since 1750, and by examining the changing theoretical perspectives that have underpinned these developments. Students will learn to re-examine the processes of contemporary science communication in the light of a deeper understanding of this history.
Interpreting Cultures is underpinned by action learning and puts contemporary curation in an international context. From the outset, students work on an interpretation intervention with one of the archives and collections on campus (such as The Stanley & Audrey Burton Gallery; Special Collections; Treasures of the Brotherton; Marks and Spencer Company Archive; ULITA ― an Archive of International Textiles; Museum of the History of Science, Technology and Medicine). This intensive experience of project planning, management, collaboration and team working prepares students for the option of undertaking a negotiated work placement in the second semester or optional modules exploring audiences, participation or engagement.
Through our Advanced Research Skills modules, students are equipped to undertake assessments and ultimately develop their own research project. The modules build to a symposium in Semester 2 where students present initial research findings towards a dissertation on a research topic of interest.
In addition, students choose from a range of optional modules offered by the School of Fine Art, History of Art and Cultural Studies and the School of Philosophy, Religion and History of Science. These include the opportunity to complete a placement or consultancy project role in either curational approaches or engagement.
You will be taught by leading researchers and experienced practitioners in their fields, and you’ll benefit from a range of teaching and learning methods. They include lectures and seminars, gallery and museum visits, as well as hands-on experience of specific collections in library sessions.
We use a range of assessment methods including essays, presentations, assignments and literature reviews among others, depending on the modules you choose.
Through a combination of theory and practice, the programme produces graduates who are able to develop professional careers in the museums and heritage sector whilst retaining a critical and reflexive eye on their own practice and that of the institutions in which they work. It will equip you with a good understanding of the issues and approaches to science communication and curation, interpretation and engagement, as well as practical work experience ― a combination which is very valuable to employers.
To get a flavour of the kinds of career trajectories our graduates of allied MAs have taken see the ‘news’ section of the Centre for Critical Studies in Museums, Galleries and Heritage and the alumni pages of the School website.
We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.
The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.
In Semester 2 you will have the option to undertake a negotiated work placement to gain first-hand experience of curating science.
We have close links with many of the major cultural institutions and organisations in the region, meaning there are plenty of opportunities for you to explore. If you have a particular ambition in mind for your placement, we usually try to find a role that suits you.
Students on allied MAs have completed placements in organisations such as Leeds City Museum, Leeds Art Gallery, Harewood House, the Henry Moore Institute, National Science and Media Museum, York City Art Gallery, National Railway Museum, Impressions Gallery, The Tetley, Yorkshire Sculpture Park, Lotherton Hall, Abbey House Museum and the Royal Armouries.
Over the last 25 years, science communication has expanded from a field of public intellectuals, celebrity scientists, broadcast media professionals and event producers to a global industry of ground-breaking artists, games developers, disruptive creators, radical curators, social entrepreneurs and citizen scientists. Developed in partnership with industry, this part-time, distance learning course will provide you with the knowledge and skills required to take advantage of excellent job prospects in this growing field.
Studying this MSc will provide you with the opportunity to accelerate your career and become part of a worldwide community which is pushing the boundaries of science communication through new and emerging technologies. You will gain practical and transferable skills informed by theory, a creative portfolio and access to world-class professional networks to progress your career in science communication. You will become mindful of the ethical challenges that new communication systems might pose to achieving sustainable development goals for health and wellbeing, gender equality and communities.
Through a selection of specifically designed modules, you will learn about the importance of involving the public in the co-creation of citizen science projects, explore the increasing trend of locating science within festivals, examine how art and science come together to innovate, and explore digital storytelling strategies for communicating science. Additionally, you will investigate how science writing and journalism has changed in a digital era, and focus on contemporary matters of global concern in science communication. All modules aim for you to develop and enhance your public portfolio through a range of creative projects.
Science communication is an expanding field and, as such, there are many exciting career prospects working in science journalism, public engagement, events production, science publishing and within the media, to name a few. Our academics have strong networks in the field and, as the course is delivered in collaboration with industry experts and professional science communicators, you can be sure that the skills and knowledge you gain are those you need to forge a successful career in the field and stay ahead of the curve. This course aims to bridge the #scicomm digital skills gap in an era where digital fluency, critical thinking, and creative innovation make professionals stand out from the crowd.
This science communication masters focuses on the areas of communication, media management, public engagement, emerging technologies, global challenges, digital literacy and creative practice.
We offer awards to help you study through our:
There are also other sources of funding available to you.
For more information please see our funding section.
This science communication MSc is designed to equip the modern science communicator with the practical skills and theoretical grounding to carry out science communication, public engagement and policy roles in a wide range of institutions, from Universities to science festivals, museums and galleries to research funders, science and health charities, NGOs and science businesses spanning education, entertainment, PR/ advocacy and sustainable development.
Science communication professionals contribute to a wide range of industries including:
Graduates could undertake roles (within these sectors and others) such as:
Data science combines computer science and statistics to solve exciting data-intensive problems in industry and in many fields of science. Data scientists help organisations make sense of their data. As data is collected and analysed in all areas of society, demand for professional data scientists is high and will grow higher. The emerging Internet of Things, for instance, will produce a whole new range of problems and opportunities in data analysis.
In the Data Science master’s programme, you will gain a solid understanding of the methods used in data science. You will learn not only to apply data science: you will acquire insight into how and why methods work so you will be able to construct solutions to new challenges in data science. In the Data Science master’s programme, you will also be able to work on problems specific to a scientific discipline and to combine domain knowledge with the latest data analysis methods and tools. The teachers of the programme are themselves active data science researchers, and the programme is heavily based on first-hand research experience.
Upon graduating from the Data Science MSc programme, you will have solid knowledge of the central concepts, theories, and research methods of data science as well as applied skills. In particular, you will be able to
The MSc programme is offered jointly by the Department of Computer Science, the Department of Mathematics and Statistics, and the Department of Physics, with support from the Helsinki Institute for Information Technology (HIIT) and the Helsinki Institute of Physics (HIP), all located on the Kumpula Science campus. In your applied data science studies you can also include multidisciplinary studies from other master's programmes, such as digital humanities, and natural and medical sciences.
Further information about the studies on the Master's programme website.
The Data Science MSc programme combines elements from computer science and mathematical sciences to provide you with skills in topics such as machine learning, distributed systems and statistical methods. You might also find that knowledge in a particular scientific field is useful for your future career. You can obtain this through elective studies in the MSc programme, or it might already be part of your bachelor-level degree.
Studies in the Data Science MSc programme include both theoretical and practical components, including a variety of study methods (lectures, exercises, projects, seminars; done both individually and in groups). Especially in applied data science, we also use problem-based learning methods, so that you can address real-world issues. You will also practise academic skills such as scientific writing and oral presentation throughout your studies. You are encouraged to include an internship in your degree in order to obtain practical experience in the field.
Elective studies give you a wider perspective of Data Science. Your elective studies can be an application area of Data Science (such as physics or the humanities), a discipline that supports application of Data Science (such as language technology), or a methodological subject needed for the development of new Data Science methods and models (such as computer science, statistics, or mathematics).
Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Data Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).
MSc in Data Science aims to equip students with a solid grounding in data science concepts and technologies for extracting information and constructing knowledge from data. Students of the MSc Data Science will study the computational principles, methods, and systems for a variety of real world applications that require mathematical foundations, programming skills, critical thinking, and ingenuity. Development of research skills will be an essential element of the Data Science programme so that students can bring a critical perspective to current data science discipline and apply this to future developments in a rapidly changing technological environment.
The MSc Data Science programme focuses on three core technical themes: data mining, machine learning, and visualisation. Data mining is fundamental to data science and the students will learn how to mine both structured data and unstructured data. Students will gain practical data mining experience and will gain a systematic understanding of the fundamental concepts of analysing complex and heterogeneous data. They will be able to manipulate large heterogeneous datasets, from storage to processing, be able to extract information from large datasets, gain experience of data mining algorithms and techniques, and be able to apply them in real world applications. Machine learning has proven to be an effective and exciting technology for data and it is of high value when it comes to employment. Students of the Data Science programme will learn the fundamentals of both conventional and state-of-the-art machine learning techniques, be able to apply the methods and techniques to synthesise solutions using machine learning, and will have the necessary practical skills to apply their understanding to big data problems. We will train students to explore a variety visualisation concepts and techniques for data analysis. Students will be able to apply important concepts in data visualisation, information visualisation, and visual analytics to support data process and knowledge discovery. The students of the Data Science programme also learn important mathematical concepts and methods required by a data scientist. A specifically designed module that is accessible to students with different background will cover the basics of algebra, optimisation techniques, statistics, and so on. More advanced mathematical concepts are integrated in individual modules where necessary.
The MSc Data Science programme delivers the practical components using a number of programming languages and software packages, such as Hadoop, Python, Matlab, C++, OpenGL, OpenCV, and Spark. Students will also be exposed to a range of closely related subject areas, including pattern recognition, high performance computing, GPU processing, computer vision, human computer interaction, and software validation and verification. The delivery of both core and optional modules leverage on the research strength and capacity in the department. The modules are delivered by lecturers who are actively engaged in world leading researches in this field. Students of the Data Science programme will benefit from state-of-the-art materials and contents, and will work on individual degree projects that can be research-led or application driven.
Modules for the MSc Data Science programme include:
- Visual Analytics
- Data Science Research Methods and Seminars
- Big Data and Data Mining
- Big Data and Machine Learning
- Mathematical Skills for Data Scientists
- Data Visualization
- Human Computer Interaction
- High Performance Computing in C/C++
- Graphics Processor Programming
- Computer Vision and Pattern Recognition
- Modelling and Verification Techniques
- Operating Systems and Architectures
The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.
As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.
- Data Analyst
- Data mining Developer
- Machine Learning Developer
- Visual Analytics Developer
- Visualisation Developer
- Visual Computing Software Developer
- Database Developer
- Data Science Researcher
- Computer Vision Developer
- Medical Computing Developer
- Informatics Developer
- Software Engineer