Post-doctoral Researcher on Multiparametric Data Analysis for Photonic Data
Post-doctoral Researcher on Multiparametric Data Analysis for Photonic Data
CIC NanoGUNE
Donostia/San Sebastian, Spain
The aim of the research project is the development of classification and regression models for data from various photonic techniques, as spectroscopy, evanescent sensing, and interferometry. The photonic data are produced by highly integrated photonic circuits that build a miniaturized gas sensing system, which is developed by several partners in the framework of a European project. NanoGUNE's part in this project is the data processing by multiparametic data analysis methods, as machine learning and deep learning.
Important tasks of the work plan
- Development of machine learning/deep learning models for classification and regression of photonic data, applying chemometric methods
- Quantification of sensing performance
- Development of data augmentation methods for spectral data
- Transfer of in silico code to on-chip Boolean computing (in collaboration with partner)
- Optimization of data fusion techniques
- Project management
Requirements
The successful candidate will preferably have a PhD in Physics, Chemometrics, Mathematics, Informatics, or related Engineering field and experience in the following skills:
- Machine learning and data analysis based on Chemometrics
- Deep learning
- Photonic methods and data
- Python and its main libraries for machine learning
- Project management
- Fluent in written and spoken English
Although not compulsory, the following points will be considered:
- Knowledge in optics, photonics, spectroscopic techniques
- Experience with interdisciplinary research
- Self-motivated and able to work in a team, coordination of research work
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