Micron’s vision is to transform how the world uses information to enrich life for all. Join an inclusive team focused on one thing: using our expertise in the relentless pursuit of innovation for customers and partners. The solutions we create help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can spark the very innovation we are pursuing.
Burn-in is the process by which components of a system are exercised prior to being placed in service (and often, prior to the system being completely assembled from those components). This testing process will force certain failures to occur under supervised conditions so an understanding of load capacity of the product can be established.
The intention is to detect those particular components that would fail as a result of the initial, high-failure rate portion of the bathtub curve of component reliability. If the burn-in period is made sufficiently long (and, perhaps, artificially stressful), the system can then be trusted to be mostly free of further early failures once the burn-in process is complete.
To facilitate Burn-In Elimination, Data Scientist will use probe data available in prior inline test to do Machine Learning and predict which die on a wafer can skip this step. Interns will work with Data Scientist and Data Engineers to process data from probe and Burn and come up with and optimize a model to predict dies which can skip burn. Intern will have the opportunity to partner with engineers from Test department as well Scientist from our Smart Manufacturing and Artificial Intelligence Team.
Required Skills and Abilities
- Major in Data Science
- Able to commit for a minimum of 3-month full-time internship, candidates available for a longer internship would be advantageous
- Proficient in Python Programming
- Job type:Internships
Data Science and Analytics
- Closing Date:17th Apr 2021, 6:00 pm