Scientist (Multi Chiplet Heterogeneous Integration and High-Speed IO Designer), (SiP), IME

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading research entity in Singapore is looking for an Electrical Modeling, Applied Machine Learning engineer. The ideal candidate will have a PhD in Electrical or Computer Engineering and strong experience in advanced packaging. Key responsibilities include developing performance models, collaborating with cross-functional teams, and integrating AI/ML solutions. The position requires proficiency in Python and statistical analysis, among other qualifications.

Qualifications

• PhD in Electrical or Computer Engineering with relevant experience.
• Understanding of advanced packaging/interconnect/I-O modelling and signal/power integrity.
• Experience in Python, statistical packages, and database management.

Responsibilities

• Develop performance models for multi chiplet advanced packages.
• Collaborate with cross-functional teams for analysis parameters.
• Integrate AI/ML solutions within the design flow.

Skills

Electrical Modeling

Applied Machine Learning

Python

Statistical Analysis

AI/ML Algorithms

Education

PhD in Electrical or Computer Engineering

Tools

Tensorflow

Scikit

PostgresSQL

Job description

We are seeking a highly skilled Electrical Modeling, Applied Machine Learning engineer to join our team. The ideal candidate will have a strong background in Electrical or Computer Engineering (PhD), with a focus on applied machine learning in advanced package physical design, high speed circuit modeling, design technology co optimization or system technology co optimization and analysis, signal / power integrity. The successful candidate will play a crucial role in developing accelerating simulation and analysis technology towards design enablement of state-of-the‑art advanced packaging.

Key Responsibilities:

• Develop performance models, feature engineering of Electrical /Thermal / Mechanical analysis of multi chiplet advanced packages
• Collaborate with cross‑functional (Electrical, Thermal and Mechanical) package design and analysis teams to ensure solid understand of the analysis parameters, input / outputs
• Data wrangling, EDA format parsing, generating custom databases for specific electrical, thermal and mechanical domain.
• Perform benchmarking of various applicable AI / ML algorithm and Design of Experiments.
• Integrate the AI / ML solution within the design flow for training and inference, develop and maintain data pipeline.
• Participate in comprehensive literature survey on diffusion models, reinforcement learning, PINN, language models and identify areas of applicability for advanced packaging electrical physical design, thermal integrity and mechanical reliability analysis
• Stay up to date with the latest advancements, improve existing models, develop new ones and propose new applicable architectures.

Required Qualifications:

• PhD in Electrical or Computer Engineering with relevant experience.
• Understanding of advanced packaging /interconnect/I-O modelling, statistical analysis, signal/power integrity, thermal flow, stress and yield factors in advanced packaging.
• Experience and Proficiency in Python, Tensorflow, Scikit, statistical packages, database SQL/no‑SQL, postgresSQL, vector databases.
• Programming and scripting skills in one or more of the following: Python, Perl, C/C++, TCL, or AEL.

Preferred Qualifications:

• Ability to research, develop and implement AI/ ML algorithms using industry‑standard open‑source tools/methodologies.
• Strong problem‑solving skills and the ability to think creatively to overcome technical challenges for cross domain implementations.
• Excellent communication and collaboration skills, with the ability to work effectively in a team environment.