Who We Are

Applied Materials is the global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to work beyond the cutting-edge, continuously pushing the boundaries of science and engineering to make possible the next generations of technology, join us to Make Possible® a Better Future.

Applied Materials’Ion Implant Particle Science groupis searching for a coop to join our team for Spring 2025! We are a small group working across several products to improve our understanding of the particle formation and transport mechanisms and thus our ability to control particles and improve yields in our semiconductor process tools.  The position will entail the following:

• Assist with particle experiments including tool preparation, interpreting designed experiment test plans, shepherding wafers.

• If necessary, design 3-dimensional (relatively simple) structures for the tool test.

• Analyzing data from particle experiments using Python, MATLAB, Excel, JMP and/or other environments.

• Presenting conclusions to the team and larger group - preparing graphs, summaries, and data presentations.

• Working with the team in building a particle library from the vast amount of historical data, which requires a great diligence and organizing skills.  Detailed instruction will be provided during the interview process.

• Working with the team to define the most effective designed experiments.

• Co-op Dates: January 27, 2025 – August 15, 2025

• On-site, Gloucester, MA

Requirements

• Student must be pursuing a Master’s degree or higher in Mechanical Engineering, Electrical Engineering, Materials Science, Physics or a related field.

• Student must be in good academic standing at their university, with a preferred GPA of 3.0 or above on a 4.0 scale.

• Knowledge of basic descriptive statistics and an interest in advanced statistical analysis.

• Capable for 3-dimensional design works such as Solidworks, Auto CAD or a related software.

• Diligent person with a good organizing skill.

• Experience in handy-on experiments preferred.

• Good communication skills.

Compensation