Associate Researcher - Data Analysis

The University of Dayton Research Institute's (UDRI) Advanced Manufacturing Technology Development (AMTD) group is seeking an engineer/scientist to drive and manage research in data analysis for metal additive manufacturing (AM). This work will advance novel research focused on sensor-based in-situ process monitoring, data correlation to end part quality, data driven machine parameterization, and data management solutions. This position will perform research designed to advance current understanding of the effects of laser manufacturing processes on materials through sensor development, implementation, data collection, and data analysis. Work activities may include:

• Developing analysis tools to extract physical meaning from in-situ process data
• Developing machine learning algorithms to drive correlation between in-situ process data and end part quality, particularly NDE
• Data fusion, registration, and calibration of various data streams
• Planning and executing design of experiments, particularly involving unique, cutting edge, LPBF strategies
• Building and routing of specimens for data collection, characterization, testing, and correlation
• Interfacing with data collection and management tools for large datasets
• Integrating and modifying in-situ process sensors
• Operating, in-situ sensors/suites for laser powder bed fusion machinery
• Developing new sensing modalities for understanding of the laser powder bed fusion process

• A bachelor's degree in engineering or computer science from an accredited University
• Coding/programming skills (python preferred)
• Effective ability to communicate both written and verbally, work well with others, and think critically and drive a project to completion with little supervision
• Due to the requirements of our research contracts with the U.S. federal government, candidates for this position must be a U.S. citizen Preferred Qualifications:

While not everyone may possess all of the preferred qualifications, the ideal candidate will bring many of the following:

• Hands on experience in the lab with custom and commercial LPBF systems and all supporting equipment
• Experience with machine learning concepts
• Experience with image processing techniques
• Experience with DREAM.3D software
• Experience performing design of experiments (DOE's) and statistical analysis
• Demonstrated experience with laser-based manufacturing equipment in support of research
• Understanding of lasers and optics
• Demonstrated experience with sensors for dynamic processes
• Understanding of laser/material interaction
• Understanding of AM process modeling tools
• Demonstrated experience with data acquisition and analysis concepts Special Instructions to Applicants