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JUNIOR SEMINAR on OCT 19th: Sn oxycarbide – structural and functional characterization of biocoatings

NOMATEN Junior Seminar on OCT 19th at 1.00PM CET (13:00) by Magdalena Gawęda PhD (Gdańsk University of Technology): "Silicon oxycarbide – structural and functional characterization of novel biocoatings. Application of vibrational spectroscopy and imaging in organic and inorganic samples analysis"

NOMATEN's new scientific paper: Nanoindentation of single crystalline Mo: Atomistic defect nucleation and thermomechanical stability

NOMATEN released new paper within the journal Materials Science and Engineering: A - "Nanoindentation of single crystalline Mo: Atomistic defect nucleation and thermomechanical stability". The authors team consist of Javier Dominguez PhD, Stefanos Papanikolaou PhD (Research Goup Leader - Materials informatics Structure and Function), Amin Esfandiarpour PhD, prof. Paweł Sobkowicz PhD DSc (Director for Scientific Operations) and prof. Mikko Alava PhD (NOMATEN CoE Director and Research Group Leader - Complexity in Materials).

 

We are hiring: jop opportunities for AI/ML Expert and Desktop Application Developer

NOMATEN plans to develop in-house functional programs and applications. We will build a software platform to facilitate data-driven methods of analyzing and predicting materials properties. Therefore, we are looking for:
- Application Developer
- Expert on artificial intelligence and machine learning to use and combine existing code, functional programs and applications, using Python, Numba and Tensorflow or Keras libraries

NOMATEN develops software for better understanding of microscopy images of materials under extreme conditions

Large Data is common across materials science. Cross-correlating and understanding data from material surfaces is very important since there is typically a direct connection to physical properties. Also, it is very important to use this data to reconstruct the actual microstructure and perform simulations in a computer at the molecular or larger scale. However, understanding of Large Data requires the application of statistical and machine learning techniques. Further, simulations require efficient microstructural reconstruction techniques. Stefanos Papanikolaou's group at NOMATEN investigates such issues.



This project has received funding from the European Union Horizon 2020 research and innovation
programme under grant agreement No 857470 and from European Regional Development Fund
via Foundation for Polish Science International Research Agenda PLUS programme grant
No MAB PLUS/2018/8.
Poland
The project is co-financed from the state budget within the framework of the undertaking of the Minister of Science and Higher Education "Support for the activities of Centers of Excellence established under Horizon 2020".

Grant: 5 143 237,70 EUR
Total value: 29 971 365,00 EUR
Date of signing the funding agreement: December 2023

The purpose of the undertaking is to support entities of the higher education and science system that have received funding from the European Union budget in the competition H2020-WIDESPREAD-2018-2020/WIDESPREAD-01-2018-2019: Teaming Phase 2. in the preparation, implementation and updating of activities, maintenance of material resources necessary for carrying out activities, acquisition and modernization of scientific and research apparatus, maintenance and development of personnel potential necessary for the implementation of activities, and dissemination of the results of scientific activities.