Summary

This module is designed for physiotherapists who wish to develop their knowledge and understanding of motor control and the underlying pathophysiology...

Motor Control in Life, Health and Disease (CHLD0025)

CELL CULTURE |NANOCOMPOSITE SCAFFOLDS|EXPERIMENT PLANNING AND ANALYSIS.

A practical introduction to experimental techniques that’s applicable to a wide range of research, including tissue regeneration and biomaterial-cell...

Tissue Culture and Bionanotechnology Techniques (SURG0085)

A practical introduction to experimental techniques that’s applicable to a wide range of research, including tissue regeneration and biomaterial-cell interactions. This module will familiarise students with the laboratory setting and develop good laboratory research practices, experimental planning techniques and the analysis of experimental results. This module will consist of lectures, workshops and practical’s.

Aims - This module aims to provide an introduction to the ideas underlying the optimal choice of component variables, possibly subject to constraints, that...

Optimisation Algorithms in Operational Research (STAT0025)

Aims - This module aims to provide an introduction to the ideas underlying the optimal choice of component variables, possibly subject to constraints, that maximise (or minimise) an objective function. The algorithms described are both mathematically interesting and applicable to a wide variety of complex real life situations. It is primarily intended for second and third year students registered on the undergraduate degree programmes offered by the Department of Statistical Science, or jointly with other departments. It also serves as an optional module for students taking the mathematics and statistics stream of the Natural Sciences degree.

Objectives - On successful completion of the module, a student should be able to understand the theoretical concepts of linear programming, dynamic programming and finite Markov programming, set up correct models of real life problems, interpret results correctly and check the validity of assumptions.

Applications - Optimisation methods provide the means for successful business strategies, scientific planning and statistical estimation under constraints. They are a critical component of any area where decision making under limited resources is necessary.

Content - Linear programming:  graphical solution techniques, simplex method, duality, sensitivity analysis. Game theory: zero-sum two player games, minimax, maximin, Laplace, Hurwicz and minimax regret strategies, linear programming formulation. Dynamic programming: systems, states, stages, principle of optimality, forward and backward recurrence. Markov sequential processes: Markov processes with rewards values-iteration, policy iteration, sequential decision processes.

Key texts - Available from ReadingLists@UCL.