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Research Fellow (3D-IC Package Fault Localisation and Failure Analysis)

Times Higher Education
23 Jan 2024

Job Information

Organisation/Company
NATIONAL UNIVERSITY OF SINGAPORE
Research Field
Engineering
Engineering
Chemistry
Engineering
Physics
Researcher Profile
First Stage Researcher (R1)
Country
Singapore
Application Deadline
Type of Contract
Other
Job Status
Full-time
Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?
No

Offer Description

Job Description

The Electrical and Computer Engineering (ECE) Department of National University of Singapore (NUS) is in search of candidate for a research fellow position to support 3D-IC package fault localisation and failure analysis (FA) techniques with Artificial Intelligence (AI)/Machine Learning (ML)/Deep Learning (DL) capability. 

You will work closely with our researchers, students, and professors, including Co-Investigators from A*STAR: I2R and IMRE, and several industry collaborators to understand and derive insights from scientific experiments and data. 

The successful candidate will be assisting in the research to enable a variation-tolerant and technology-agnostic ML guided system to achieve 10x or greater reduction in time taken for FA process; reducing from weeks/months of fault identification to hours. This in turn allows problems to be identified and resolved quickly leading to faster time-to-market, yield and productivity improvements.

Responsibilities will involve:

  • Develop magnetic field imaging (MFI) workflow and perform correlative study with Lock-in Thermography (LIT).
  • Develop ML algorithms to guide MFI data processing.
  • Develop ML algorithms to capture X-ray image of 3D-IC defects.
  • Develop ML algorithms to extract features and identify defects.
  • Develop 3D-IC forward predictive models (i.e. include chip and circuit blocks) and ML feature set to integrate with MFI tool interfaces.
  • Lead research article publications and invention disclosures.
  • Lead new equipment purchases and commissioning.
  • Assume super-user role of multiple equipment (ownership and maintenance) and leadership role for safety.
  • Provide trainings and certifications to new users.

(Interested applicants should send their curriculum vitae via email to eleykl@nus.edu.sg).

Qualifications

  • PhD in Electrical, Electronics, Mechanical, Chemical Engineering, Physics, Material Science or its equivalent from a reputable University/Institute is preferred, or equivalent related experience. 
  • Candidate with experience in microelectronic research, characterisation, metrology, electrical testing, FA and strong in data analysis will have advantage. Knowledge of AI/ML/DL development and TCAD modelling. 
  • Strong analytical and problem-solving skills.
  • Motivated and possesses effective communication skills including writing and presenting.
  • Ability to work independently and collaborate within a diverse team.
  • Open to Fixed Term Contract

More Information

Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department : Electrical and Computer Engineering
Employee Referral Eligible: No
Job requisition ID : 23132

Requirements

Additional Information