Imperial College London

ProfessorSimonSchultz

Faculty of EngineeringDepartment of Bioengineering

Professor of Neurotechnology
 
 
 
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Contact

 

s.schultz Website

 
 
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Location

 

4.11Royal School of MinesSouth Kensington Campus

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Summary

 

Mathematical Methods for Bioengineers - BIOE97141

Aims

This module introduces the choice and use of appropriate mathematical modelling to model biological systems and analyse complex biological data. Learning outcomes To formulate bioengineering problems in terms of appropriate mathematical modelling methods. To analyse biological data using appropriate mathematical methods To evaluate the output of the mathematical modelling methods in relation to the underlying biological processes To evaluate the best mathematical method for addressing a particular bioengineering problem To critically evaluate the output of mathematical analysis of a bioengineering problem To encode mathematical models using MATLAB or Python To manipulate experimental data using mathematical methods

Role

Lecturer

Statistics and Data Analysis - BIOE97049

Aims

For those who have not met probability statistics before: to enable an understanding of the very basics of statistical analyses in common use in the biomedical engineering sciences, whilst at the same time, presenting a fresh view of statistical concepts. For those who have met statistics before: to give some familiarity with the resources available for performing data and statistical analyses which typically enable more flexibility than is normally found in off-the-shelf packages, such as SPSS.

 

Role

Lecturer