Master’s project

Master’s project

Ferroelectric memory optimization and automation of the X-ray characterization workflow

Ref. 2024_010

About Us

IBM Research Europe - Zurich is a vanguard of European research, shaping future technologies through dynamic collaborations with academia and industry. We are dedicated to advancing Artificial Intelligence (AI) and Neuromorphic Computing, addressing critical issues such as power consumption and computing time.[1]

Ferroelectric memory devices, known for their energy efficiency and CMOS compatibility, are promising for AI hardware, especially in deep neural network acceleration.[2,3] This project offers you the chance to establish a metrology framework for assessing the quality of interfaces and layer properties in devices like ferroelectric tunnel junctions (FTJs)[2] and ferroelectric field-effect transistors (FeFETs)[3] using X-ray reflectometry and diffractometry measurements[4]. Your insights, along with transmission electron microscopy (TEM) images, will refine ferroelectric metal-oxide growth parameters to enhance device performance.

Join our dynamic environment, where you will collaborate closely with leading experts in material development and cutting-edge memory technologies designed for analog AI. We invite you to embark on this exciting semester-long project.
Please note that as this position is related to a Master’s project, a financial compensation is not provided.

Role

In the frame of this project, you will undertake pivotal tasks including the assessment of ferroelectric film quality and the automation of the XRD characterization. Additionally, you will spearhead the development of a user interface to control tool parameters, streamlining processes and enabling predictive maintenance. You will have access to cutting-edge research facilities, including the ETH/IBM BRNC cleanroom, and will gain invaluable experience in instrument measurements and data analysis while collaborating with a diverse and innovative team.

Profile

• Enrolled in a Master’s program in Electrical Engineering, Physics, Neuroscience, or related fields.
• Proficient in written and spoken English.
• Proficient in MATLAB and/or Python programming.
• Background in Material Science is advantageous.
• Prior internship or industrial experience preferred but not required.

This is your chance to contribute to cutting-edge research and be part of a team working on the future of computing.

Diversity

IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent flexible working arrangements enable all genders to strike the desired balance between their professional development and their personal lives.

How to apply

If you are interested to apply, please submit a motivation letter and your CV through the link below.
We wish you all the best for your Master degree and are looking forward to hearing from you!

If you have any questions, please contact Marilyne Sousa, sou @zurich.ibm.com and Dr. Saketh Ram Mamidala, saketh.ram.mamidala @ ibm.com .

References
[1] A. Sebastian, M. L. Gallo, R. Khaddam-Aljameh and E. Eleftheriou, Nat. Nanotechnol., 2020, 15, 529-544
[2] L. Bégon-Lours, M. Halter, Y. Popoff, Z. Yu, DF Falcone, D. Davila, V. Bragaglia, A. La Porta, D. Jubin, J. Fompeyrine, B. J Offrein IEEE J. Electron Devices Soc., 2021, 9, 1275-1281
[3] M. Halter, L. Bégon-Lours, V. Bragaglia, M. Sousa, BJ Offrein, S. Abel, M. Luisier, J. Fompeyrine ACS Appl. Mater. Interfaces, 2020, 12, 17725-17732
[4] Birkholz, M., Thin Film Analysis by X-Ray Scattering, 1st ed.; Publisher: WILEY-VCH Verlag GmbH & Co.KGaA, 2006

In your application, please refer to myScience.org and reference  JobID 2908323 .