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Thesis topic proposal
 
Károly Héberger
Development and testing multivariate chemometric models

THESIS TOPIC PROPOSAL

Institute: University of Pécs
chemistry
Doctoral School of Chemistry

Thesis supervisor: Károly Héberger
Location of studies: MTA TTK
Abbreviation of location of studies: MTA


Description of the research topic:

Multivariate methods for data analysis are to be developed, tested (e.g. supervised and unsupervised pattern recognition methods: principal component analysis, linear discriminant analysis, partial least squares regression, artificial neural networks, classification and regression trees, random forest, support vector machines, etc.) Moreover, homemade algorithms are elaborated for variable selection, for comparison, ranking and grouping of models, features and methods. The chemometric methods are applied for various data sets and matrices (NIR spectra, hyphenated techniques with mass spectral detection, sensory evaluations in food chemistry, chromatographic data, quantitative structure - activity relationships and so on. Programming knowledge is not mandatory, but advantageous


Deadline for application: 2017-01-31

 
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