DCS Corporation has an opportunity for a Research Scientist to support basic and applied research and analysis efforts in our Dayton, OH office. Our team is developing discrete and continuous optimization algorithms and software products in support of research in the areas of cooperative control and air vehicle autonomy. The software/algorithms are being developed in Python, Julia, and/or C++, and are implemented on-board on autonomous air-vehicles.

Essential Job Functions:

In this role, you will have the opportunity to support activities in the following areas:

Understanding AFRL application requirements and identifying research gaps in the area of cooperative control and path planning.

Developing mathematical models that represents the physical systems with reasonable accuracy and are applicable to fixed-wing aircraft.

Formulating problems using the models developed and analyzing/solving using continuous and discrete optimization methods.

Developing algorithms and software codes using the solution methodologies such as sampling-based planners for route/motion planning

Developing and implementing Monte-Carlo simulations to empirically evaluate the performance of the algorithms.

Documenting the findings and results for publishing in technical journals and conference.

Assisting in integration of the developed algorithms with AFSIM or UxAS (AFRL simulation tools), and on-board implementation for flight testing.

You could anticipate being asked to:

Develop software in Python, Julia, and/or C++ implementing continuous or discrete optimization methods.

Participate within a software development team to design, develop, test, and deploy developed planning algorithm.

Interact with government and industry customers to define requirements and meet analytic needs.

Present results of the team's development activities to government and industry customers.

Some short-term travel may also be requested of you, from time to time.

Required Skills:

Due to the sensitivity of customer related requirements, U.S. Citizenship is required.

At least an MS degree in engineering, mathematics, computer science, or related technical discipline and at least one year of related experience (a focus on optimization is preferred)

Applicants selected will be subject to a U.S. Government background investigation and must meet eligibility requirements for access to classified information: must be able to attain at least a Secret level security clearance.

Experience developing software using programming languages such as Python, Julia, or C++.

Ability to work well in team-oriented environments.

Ability to travel, if needed.

An ideal candidate would also bring the following qualities, but not required:

Knowledge of AFSIM and UxAS is a plus, but not required.

Proficiency solving mathematical and physics-based problems of moderate to high complexity.

Experience with software version control tools (Git etc.).

Domain knowledge related to machine learning.

Domain knowledge in an engineering discipline relating to aerospace and defense (e.g., Aero, G&C, EE).

PhD in engineering, mathematics, computer science, or related technical discipline