Postdoctoral researcher in multiparametric data analysis for photonic data at CiC NanoGUNE
The Nanoscience Cooperative Research Center, CIC nanoGUNE, located in Donostia / San Sebastian, Basque Country (Spain), is now looking for a Post-doctoral researcher to work on Multiparametric data analysis of photonic data
NanoGUNE is a research institute dedicated to undertaking world-class nanoscience research to help the Basque Country flourish competitively. NanoGUNE is a Basque Research and Technology Alliance (BRTA) member and a María de Maeztu Unit of Excellence, as acknowledged by the Spanish Research Agency.
Prof. Andreas Seifert (a.seifert@nanogune.eu) directs the Nanoengineering Group, which is hiring. The Nanoengineering group does research in optics and photonics, with multidisciplinary connections to nanotechnology, other engineering domains, and machine learning. A special emphasis is on the use of artificial intelligence with photonic data.
The candidate will join a highly diversified research group that specializes in spectroscopic and other photonic technologies for biomedical research, environmental monitoring, and different detection methods, with chemometric support. More information is available at https://www.nanogune.eu/nanoengineering.
The goal of the research project is to create classification and regression models for data collected using various photonic techniques such as spectroscopy, evanescent sensing, and interferometry. The photonic data are generated by highly integrated photonic circuits that form a tiny gas sensing device created by multiple partners as part of a European project. NanoGUNE’s role in this project is to process data using multiparametric data analysis approaches such as machine learning and deep learning.
Important duties in the work plan
- Development of machine learning/deep learning models for categorization and regression of photonic data using chemometric approaches.
- Quantification of Sensing Performance
- Developing data augmentation approaches for spectral data
- Transferring in silico code to on-chip Boolean computing (collaboration with partner)
- Optimization of data fusion techniques.
- Project Management
- The successful candidate should have a PhD in Physics, Chemometrics, Mathematics, Informatics, or a related Engineering subject, as well as competence in the following skills:
- Chemometric Machine Learning and Data Analysis
- Deep learning uses laser algorithms and data.
- Python’s key libraries for machine learning
- Project Management
- Fluent in written and spoken English.
Although not required, the following points will be considered:
- Knowledge of optics, photonics, and spectroscopic techniques
- Experience in multidisciplinary research.
- Self-motivated and capable of working in a team; coordination of research work
We encourage teamwork in a varied and inclusive atmosphere and welcome all applications, regardless of age, disability, gender, nationality, color, religion, or sexual orientation.
The earliest start date for this post is October 1, 2024. The project will end in May 2028.
Candidates should apply by submitting the following documents: a complete CV, motivation letter, certifications, and two references, all in one PDF file, by clicking the Apply here button.
The application date is September 22, 2024.