Additive Manufacturing Researcher, Data Analysis

University of Dayton, Ohio•Dayton, OH

About The Position

Position Summary: The University of Dayton Research Institute's (UDRI) Additive Manufacturing Technology Development (AMTD) group is seeking an engineer/scientist to drive and manage research in data analysis for metal additive manufacturing (AM). UDRI is a national leader in scientific and engineering research, serving government, industry and nonprofit customers. This is a full time benefit eligible position that offers health, dental and vision insurance, retirement, disability, vacation and sick accrual and paid Holidays. Join the UDRI team as an Additive Manufacturing Researcher, Data Analysis and apply today! 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 the following. 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.

Requirements

3 years of experience in metal additive manufacturing or related field.
Leadership or technical mentoring experience, ability to work in a team environment, and the ability to provide technical leadership for supporting personnel and collaborators.
A bachelor's degree in engineering or computer science from an accredited University.
Coding/programming skills.
Effective written and verbal communication skills
Ability to work well with others
Strong critical thinking skills
Ability to 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.

Nice To Haves

Graduate degree in engineering or computer science.
Publications in the field of in-situ sensing for LPBF.
Proven management capabilities of research projects.
Ability to drive new research funding and collaboration opportunities for growing advanced material AM program at UDRI.
Understanding of LPBF material and part quality considerations.

Responsibilities

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.