The aim of this module is to develop student’s ability and confidence in communicating science, complex information, knowledge and concepts using a variety of communication methods. The module also aims to develop student’s coding and data analysis abilities, as well as softer professional skills.

These link to the requirements in the QAA Materials benchmark statement of 2017, in particular 3.4.vi, computational simulation of materials across the lengthscales and corresponding timescales from atomistic (classical and quantum) to finite elements

It will also contribute to the students’ fluency in mathematics, and familiarity with a range of mathematical and computational methods, for expressing the laws of science, for formulating and solving problems.

• Data collection and processing
• Data reporting and presentation
• Statistical analysis methodologies
• Presenting technical reports and complex data in a variety of ways (e.g. posters and oral presentations)
• Summarising large datasets in logical manner and presenting them in a coherent way
• Relating different datasets to extract the information required, for example the remaining lifetime in a structural component
• Learn to distinguish the characteristics of true from false data points and understand the concept of experimental error and statistical margins

• Communicate scientific information and complex concepts effectively either in writing or orally
• Apply standard statistical and mathematical approaches to analyse and process data
• Apply computer programming to carry out simple tasks
• Present themselves and their background through the writing of curriculum vitae and cover letters
• Work effectively in a group to solve problem sheets and present information
• Use appropriate visual methods of communicating data

• Apply knowledge of mathematics, statistics, natural science and engineering principles to the solution of complex problems. Some of the knowledge will be at the forefront of the particular subject of study (C1)
• Analyse complex problems to reach substantiated conclusions using first principles of mathematics, statistics, natural science and engineering principles (C2)
• Select and apply appropriate computational and analytical techniques to model complex problems, recognising the limitations of the techniques employed (C3)
• Select and evaluate technical literature and other sources of information to address complex problems (C4)
• Use a risk management process to identify, evaluate and mitigate risks (the effects of uncertainty) associated with a particular project or activity (C9)
• Adopt an inclusive approach to engineering practice and recognise the responsibilities, benefits and importance of supporting equality, diversity and inclusion (C11)
• Apply knowledge of engineering management principles, commercial context, project and change management, and relevant legal matters including intellectual property rights (C15)
• Function effectively as an individual, and as a member or leader of a team (C16)
• Communicate effectively on complex engineering matters with technical and non-technical audiences (C17)
• Plan and record self-learning and development as the foundation for lifelong learning/CPD (C18)
• Select and critically evaluate technical literature and other sources of information to solve complex problems (M4)
• Use a risk management process to identify, evaluate and mitigate risks (the effects of uncertainty) associated with a particular project or activity (M9)
• Adopt an inclusive approach to engineering practice and recognise the responsibilities, benefits and importance of supporting equality, diversity and inclusion (M11)
• Apply knowledge of engineering management principles, commercial context, project and change management, and relevant legal matters including intellectual property rights (M15)
• Communicate effectively on complex engineering matters with technical and non-technical audiences, evaluating the effectiveness of the methods used (M17)
• Plan and record self-learning and development as the foundation for lifelong learning/CPD (M18)