Position summary

Integration of Augmented and/or Virtual Reality software with robotic operations. We will be developing a complex system that allows a user to interact with a simplified UI in either AR or VR to designate areas of an object a robotic system must cover during an operation. These user commands will need to be translated into transforms and robotic programming to assign tasks to a robotic system and allow it to intelligently recreate the user actions in an optimal and efficient way. 

Anticipated duties and responsibilities

• Testing of various hardware and software applications to identify the best methods of integrating AR/VR and Robotic hardware systems.
• Development of software code to integrate user actions in AR/VR type system with commands used for robotic operation.
• Development and testing of methods to translate user actions into optimized robot path planning algorithms. 

Qualifications

Minimum

• Programming experience with robotic systems

Preferred

• Experience with integrating external systems with robotics

Required

• Due to the requirements of our research contracts with the U.S. federal government, candidates for this position must be a U.S. citizen.

Position summary

We are looking for a UD faculty member with expertise in computational modeling of laser powder bed fusion (LPBF) metal additive manufacturing processes. With industry driven interest in new and advanced AM processing levers for increased throughput (i.e. ring lasers), models that assist in bounding the processing parameter space will be instrumental to future adoption. Specifically, advanced sensor technology and constitutive material modeling are needed to understand the melt pool volume (width, depth, & length) and thermal gradients associated with cooling.

Anticipated duties and responsibilities

Collaborate with the Advanced Manufacturing Technology Development group staff to develop a research plan including:

• LPBF builds with advanced alloys
• In-situ thermal sensors for characterizing the melt pool
• Modeling activities to identify the narrow processing window parameters for successful AM prints with minimal voids and cracks

Qualifications

Minimum

• Familiarity with LPBF metal additive manufacturing processes
• Experience in computational modeling tools for melt pool simulations

Preferred

• Experience developing physics-based software tools for advanced melt pool simulations

Position summary

We are looking for a UD faculty member with expertise in product design and additive manufacturing (AM) for both metals and polymers.  With additive manufacturing technologies progressing through the TRL and MRL levels, they are becoming more common place as manufacturing methodologies yet engineers don’t have experience designing for the processes.  As well, there is a future supply chain gap in trained equipment operators.  This collaboration will help understand manufacturing limits and drive common, standardized, documented design practices leading to industry standards for all to use with this technology.

Anticipated duties and responsibilities

Collaborate with the Sustainment Technologies Division and the Advanced Manufacturing Design group to perform the following:

• Create and execute a Design of Experiments (DoE) to understand the build limitations of the Concept Laser M2 LPBF AM printer and the eos P810 SLS AM printer
• Research where work is being done in AM in alignment with national standards and align UDRI for input
• Create design rule books for metal and polymer AM utilizing DoE data as well as historical data for LPBF, FDM and SLS processes
• Create certification level course (possibly online) around design for AM
• Investigate operator level courses for the eos M290 and the possibility of UDRI being a certified operator training resource for eos

Qualifications

Minimum

• Experience with additive manufacturing of polymers (FDM)
• Experience with additive manufacturing of metals (LPBF)
• Experience with Design of Experiments (DoE)
• Experience with product design

Preferred

• Experience with technical writing
• Experience with course development
• Experience with national standards

Position Summary

The Air Force Digital Transformation Office (DTO) has asked UDRI to assist with the collaboration of government, industry and academia to accelerate digital transformation and digital modernization across Air Force and Army elements. The University stood up a seedling facility to kick off the initiative which will grow into a larger capability over time. The DTO team would like UDRI to develop and execute “Collider” events, facilitate connections to the community, and develop curricula for workforce development. The collider events could include events to bring together pre-college, university, STEM and potentially CTC engineering and computer science departments to participate in competitions supporting emerging technology and tech reuse. This role would focus on identifying opportunities and organizing collider and other events with these organizations in the Dayton region. Additionally, the role would support identification of strengths and weaknesses of UDRI and UD in the digital transformation community and lay out approaches to capitalize on strengths and shore up weak areas for continued growth in digital transformation support to the military services.

Anticipated duties and responsibilities 

• Interface with local educators to develop opportunities for involving STEM in current curricula
• Identify outreach opportunities within the Dayton community
• Research what other universities and innovation centers are doing to enhance STEM and drive Digital Transformation across the region.
• Develop and execute Collider and training events with the local education community
• Develop a path forward for growing UD’s reputation nationally in digital transformation training and implementation

Qualifications 

MINIMUM 

• Knowledge of digital transformation technologies including model-based systems engineering (MBSE)
• Ability to drive collaboration with academic organizations

PREFERRED 

• Knowledge of emerging technologies and their potential application within the Air Force
• Connection with local education community

REQUIRED 

• Due to the requirements of our research contracts with the U.S. federal government, candidates for this position must be a U.S. citizen.

Position summary

UDRI completed a successful IRAD during the summer of 2023 in the research areas of federated learning and edge/distributed computing. A Federated Learning for Autonomy Testbed (FLATbed) was created and is currently being utilized. UDRI conducts a wide range of research for our DoD customers, and is often thought of as a member of the ‘in-house’ team. However this closeness to DoD customers and thinking often precludes UDRI from directing our own research and from generating ideas that are ‘unique and innovative’ from the perspective of DoD. DoD often uses unique and innovative ideas as part of its scoring metric for white papers and proposals, and UDRI often struggles in this area. This novel approach/algorithm will serve as a unique and innovative idea, which will elevate the status of UD/UDRI within these spaces.

Anticipated duties and responsibilities

• Conduct research in federated learning
• Create a novel algorithm(s)/publishable research to elevate UD/UDRI status in the field
• Implement and test created algorithms in Python within FLATbed

Qualifications

Minimum

• Faculty member must be knowledgeable in machine learning and low size, weight and power (SWaP) approaches to edge computing
• Faculty member must be experienced in creating algorithms with the Python programming language

Preferred

• Faculty member should have prior experience working specifically with the type of machine learning known as federated learning.