Postdoctoral Researcher – Advanced Electron Nanoscopy

Description of Group/Project:
1) Single atom recognition and localization in embedded quantum and nanostructures. From the atomic resolution data we obtain in the aberration corrected advanced electron microscopes we create 3D atomic models of the nanosystems studied. In this way, we can get full knowledge of the crystal structure, morphology and composition at the atomic scale allowing to understand the growth mechanisms of nanomaterials. We have been able to understand the mechanisms of the polarity-driven growth in free-standing nanostructures like nanowires, nanobelts, and tripods or 2D nanomembranes, or setting paths for the van der waals epitaxy growth mechanisms of semiconductor and oxide nanostructures.
2) Development of methodologies to perform a direct correlation between the structure and elemental composition at the atomic scale and the physical properties at sub-nanometer scale: the new advances in energy resolution in electron microscopy allows us to perform detailed in-situ studies of the photonic, plasmonic and even phononic properties of the nanomaterials, correlated to simulated theoretical models (e.g.: nanosystems for quantum computing, electronics and photonics).
3) Development of in-situ / in-operando experiments in the TEM to understand the physical and chemical phenomena promoting energy mechansims (e.g.: photoelectrochemical) with unprecedented resolution, allowing to correlate the theoretical models with the in-situ TEM and Synchrotron experiments.

Main Tasks and responsibilities:
Within the groups main research lines the candidate will work on the development of AI enhanced atuomated tools for STEM data analysis, including images and spectra. One of the objectives will be applying these tools to the automation of in-situ characterization, including (photo)catalysis experiments in the STEM. The automation of data will include EELS spectra and atomic resolution images. The project will include se in-situ tests on catalytically active materials. The position will include a secondment at ER-C Jülich.

Requirements:
· Education: PhD in Materials Science, Physics, Chemistry or similar
· Knowledge and Professional Experience: expert in STEM, EELS, data analysis, Python based coding of AI ML/DL tools for automated STEM data analysis.
Python programming, STEM advanced hands-on, plus advanced data analysis skills (EELS, GPA, EDX, atomic resolution images).
· Personal Competences: Teamwork skills, Fluent English (both spoken and written)

Summary of conditions:
· Full time work (37,5h/week)
· Contract Length: Temporary (6 months)
· Location: Bellaterra (Barcelona)
· Salary will depend on qualifications and demonstrated experience.
· Support to the relocation issues.
· Life Insurance.

Estimated Incorporation date: as soon as possible

Proyecto PID2020-116093RB-C43 financiado por MCIN/ AEI /10.13039/501100011033.

The IMPRESS project has received funding from the European Union’s Horizon Europe framework program for research and innovation under grant agreement n. 101094299. Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.

How to apply:
All applications must be made via the ICN2 website and include the following:
1. A cover letter.
2. A full CV including contact details.
3. 2 Reference letters or referee contacts.

Deadline for applications: 27 June 2024

Equal opportunities:
ICN2 is an equal opportunity employer committed to diversity and inclusion of people with disabilities.
ICN2 is following the procedure for contract of people with disabilities according with article 59 of the Royal Decree 1/2015, of 30 of October.