Overview:

The first few lectures of this module present an overview of biomaterials, including the properties of natural biomaterials such as skin, bone, hair...

Overview:

The first few lectures of this module present an overview of biomaterials, including the properties of natural biomaterials such as skin, bone, hair etc. Metallic biomaterials, including stainless steel and titanium are discussed. This is followed by a few lectures on other metallic alloys such as Co-Cr-Mo. The use of metals in orthopaedic prostheses for the knee, shoulder and hip as well as in fracture fixation devices are critically reviewed. An insight into the types of polymers and their potential applications as biomaterials is presented, including polymer devices. Using a case study (such as shape memory polymers) developmental stages during the design and synthesis of a biomedical polymer are elucidated.

Methods of analysing biomedical polymeric materials from the laboratory to in-vitro testing are described. Examples of how degradation of polymeric materials can be useful or harmful to their surroundings and methods which have been developed to overcome such issues are discussed. Bioceramics are discussed in detail, including a case study on hydroxyapatite. A few lectures cover the development of composites for biomedical applications.

The module covers details of biomaterials processing, forming and relating manufacturing. The module is boosted by supplementary lectures on clinical biomaterials and bioengineering from the Professor of Engineering and Surgery in the UCL Department of Mechanical Engineering who is also a Consultant Vascular Surgeon at The Leeds General Infirmary.

Aims: This is a mathematically rigorous, theoretical module on the main econometric tools needed to read and write research papers in economics. The module...

Aims: This is a mathematically rigorous, theoretical module on the main econometric tools needed to read and write research papers in economics. The module covers leading methods for formulating econometric models, estimating their parameters and performing statistical inference. The techniques are specialized according to different types of data, including cross-sectional and time-series data. The module makes extensive use of linear/matrix algebra, statistical inference and some multivariable calculus. Since this is primarily a theoretical module, the assumption is that students have some training in undergraduate econometrics to provide them with motivation and examples.

The focus is more on formal mathematical derivations and analytical rigor, rather than on examples of applications of the techniques.

Suitable for: UCL MSc Economics students, UCL MSc Data Science and Public Policy (Economics route) students.

 