Postdoc: High-Throughput Magnetic Thin Films Discovery

CNRS - National Center for Scientific Research; France; Sur place; EUR 38 000 - 46 000; Plein temps

Résumé du poste

CNRS at Institut Néel invites a post-doctoral researcher to advance high-throughput fabrication and characterization of magnetic thin films. The project focuses on commissioning an in-house magneto-optical magnetometer within the MNM / Micro and Nano Magnetism team, contributing to a data-driven development program in condensed matter physics.

The candidate will implement experimental protocols, optimize sputtering of graded films, and explore substitution effects while applying ML data

Qualifications

• PhD in experimental physics or materials science.
• Solid basis in magnetism.
• Hands-on experience with Magnet Optical Kerr Effect magnetometry.
• Experience in thin film fabrication and characterization of structural and magnetic properties.
• Experience with coding (Python) for data analysis.
• Good spoken and written English.
• Good communication skills, ability to write reports/articles.
• Team work.

Responsabilités

• Commissioning of equipment
• Development of experimental protocols
• Sputtering of compositionally graded thin films
• Structural (XRD, SEM, profilometer…) and magnetic (MOKE, characterization...)
• Data analysis using both conventional and machine learning approaches
• Supervision of intern(s)

Connaissances

Magnetism

MOKE magnetometry

Thin film fabrication

Python (data analysis)

English communication

Team work

Data analysis

Formation

PhD in experimental physics or materials science

Outils

XRD

SEM

Profilometer

MOKE instrumentation

Description du poste

CNRS at Institut Néel invites a post-doctoral researcher to advance high-throughput fabrication and characterization of magnetic thin films. The project focuses on commissioning an in-house magneto-optical magnetometer within the MNM / Micro and Nano Magnetism team, contributing to a data-driven development program in condensed matter physics.

The candidate will implement experimental protocols, optimize sputtering of graded films, and explore substitution effects while applying ML data