Design and Modeling Engineer - E3

at  Applied Materials

We are working on exciting projects, connecting materials to systems, to drive new innovations that enable the growth of Artificial Intelligence. You can be part of this cutting-edge DTCO team, in designing new logic, memory, power, packaging technologies that moves the industry forward on AI. You will have the opportunity to design transistors, DRAM, NAND, SiC, GAN, PCBs and Packages, in a co-design manner that significantly improves the system Power, Performance and Area. In this role, you will focus on atomistic modeling and simulations of future technologies.
we are seeking therfore, an experienced Atomic-scale Simulation Engineer specializing in semiconductor technology and related fields. The ideal candidate possesses a strong background in state-of-the-art computational techniques such as ab-initio quantum mechanical, classical molecular dynamics, Monte Carlo simulations, and acquainted with data analysis and machine learning. The primary job responsibility is to perform advanced modeling and simulation of critical material properties (electronic, structural, magnetic, thermal, etc.) and identify the potential impact on emerging logic and memory device applications prior to the availability of experimental data.
The objective of the Design Technology Modeling team is the development of advanced material simulations that capture as much of the physics as possible. To achieve this, we are integrating a range of multiscale simulation methodologies, from ab-initio atomistic DFT to continuum circuit level. Our goal is to accelerate semiconductor materials research and development and simultaneously advance new Design Technology Co-Optimization (DTCO) solutions to drive leading-edge semiconductor device technology.
The ideal candidate possesses a wealth of knowledge and experience, accumulated through extensive collaboration with diverse hardware teams, that will guide, motivate, and inspire others to continue to strive for, and achieve success.

ESSENTIAL REQUIREMENTS AND FUNCTIONS:

• PhD in Materials Science, Physics, Computational Chemistry, EE (or equivalent fields and experience)
• Use hierarchy of simulation models to provide expert input and technical advice to hardware design team.
• Provide fundamental understanding on Electron transport (with NEGF) for resistivities, Schottky Barrier tuning at interface models, Work function engineering, leakage current extraction, ion-diffusion models.
• Expert on formation energy simulations with dopant/impurities.
• Expert on atomistic design of surfaces, interfaces, multi-stack models, and polycrystalline materials.
• Ability to utilize new materials such 2D-material or nanotube materials for advanced memory and logic devices.
• Expertise in computational simulation platforms such as QuantumATK, VASP, LAMMPS, GAUSSIAN, Lattice Kinetic Monte Carlo.
• Use of Microsoft Office tools (Word, Excel, PowerPoint) and proficiency in writing for reporting
• willingness to work in a fast-paced, deadline-driven environment
• Strong knowledge of problem analysis and diagnosis technique
• Strong communication skill and good teamwork skills in working together to achieve goals.

QUALIFICATIONS WE DESIRE:

• Experience with high-performance computing environments.
• Experience in programming languages with Fortran, Python, Matlab, etc.
• Development of Force Field with Machine Learning methods for classical molecular dynamics simulations.
  Qualifications

EDUCATION:

Doctorate Degree

YEARS OF EXPERIENCE:

7 - 10 Years

WORK EXPERIENCE:

Additional Information

• Collaborate with collaborators to evaluate the process risk and propose solutions by performing Atomic-scale Simulations.
• Build and maintain physical models at difference scopes to perform troubleshooting on new process problems as related to design, material, or process.
• Contribute to build the DTCO (Design Technology Co-Optimization) simulation platform to enable efficient evaluation and down-selection of new materials and other process options using PPAC (power, performance, area and cost) design metrics.
• Work with software vendor to improve the modeling capability