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Förslaget inkom 2004-09-29

Modelling and analysis of high order chemical data

OBS! ANSÖKNINGSTIDEN FÖR DETTA EXJOBB HAR LÖPT UT.
This diploma work aims at elucidating the possible advantages of linear high-order or Non-linear modelling of 1H-NMR (Nuclear Magnetic Resonance) data of biofluids colleted in pseudo-time series as opposed to unfolding and conventional projection of data. The project incorporates the use of modelling methods such as PARAFAC/CANDECOMP models and SOM networks (Self-Organizing Maps). The work is in the context of metabolite tracing in the area of drug development. The data are already acquired (600MHz) so no instrument or sample handling is necessary. The problems are of great importance for the industrial/modelling community and the results should draw considerable interest.

The applicant should, preferably, have a strong interest in mathematical modelling, and an interest in statistics and chemistry. Good programming skills are necessary (Matlab) since new visualization tools/modelling approaches are expected to emerge from this work. The work will be performed at the Stockholm University. There also exist an opportunity to collaborate with a leading group in Europe in the field of Neural Networks.


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