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ADVANCED TECHNOLOGY CENTER has floated a tender for Development of Computational Algorithms for One-Dimensional and Multidimensional Data Analysis and their Visualization for Creating Software (Software). The project location is Uzbekistan and the tender is closing on 07 Nov 2025. The tender notice number is 25110012457344, while the TOT Ref Number is 129317142. Bidders can have further information about the Tender and can request the complete Tender document by Registering on the site.
Procurement Summary
Country: Uzbekistan
Summary: Development of Computational Algorithms for One-Dimensional and Multidimensional Data Analysis and their Visualization for Creating Software (Software)
Deadline: 07 Nov 2025
Other Information
Notice Type: Tender
TOT Ref.No.: 129317142
Document Ref. No.: 25110012457344
Financier: Self Financed
Purchaser Ownership: Public
Tender Value: UZS 831250000
Purchaser's Detail
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Login to see detailsTender Details
Design and implement a modular library of original, flexible and scalable computational algorithms in MATLAB or Python for single- and multivariate data analysis. Algorithms must correctly handle large-scale data sets typical for research in natural sciences. and engineering sciences, and cover advanced methods of data diagnostics, transformations, classical statistical tests, effect size estimation, multiple comparison procedures, error control, regression, classification, decomposition, clustering, and chemometric pattern recognition. The library must be extensible, numerically robust, well documented (with proven applicability on large-scale experimental datasets), and ready for integration into graphical user interface (GUI) software.
Design and implement a modular library original, flexible and scalable computational algorithms in MATLAB or Python for one- and multivariate data analysis. Algorithms must be able to handle large-scale data sets typical of science and engineering research and cover advanced techniques data diagnostics, transformations, classical statistical tests, effect size estimation, multiple comparison procedures, error control, regression, classification, decomposition, clustering and chemometric pattern recognition. The library must be extensible, numerically robust, well documented (with proven applicability on large-scale experimental data sets) and ready for integration into GUI software (GUI).
Bid Evaluation Method: Lowest Price Method
Status: Published
Source of funding: Loyiha mablaglari doirasida
Documents
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