Hiring.Camp

Pre-Award: MXM- Scientist III

Barbaricum

·

Today

Location
Crane, IN
Workplace
Onsite
Department
Mission Support
Experience
10+ years
Education
PhD
Clearance
Required
Source
Greenhouse

Description

Barbaricum is a rapidly growing government contractor providing leading-edge support to federal customers, with a particular focus on Defense and National Security mission sets. We leverage more than 17 years of support to stakeholders across the federal government, with established and growing capabilities across Intelligence, Analytics, Engineering, Mission Support, and Communications disciplines. Founded in 2008, our mission is to transform the way our customers approach constantly changing and complex problem sets by bringing to bear the latest in technology and the highest caliber of talent.

Headquartered in Washington, DC's historic Dupont Circle neighborhood, Barbaricum also has a corporate presence in Tampa, FL, Bedford, IN, and Dayton, OH, with team members across the United States and around the world. As a leader in our space, we partner with firms in the private sector, academic institutions, and industry associations with a goal of continually building our expertise and capabilities for the benefit of our employees and the customers we support. Through all of this, we have built a vibrant corporate culture diverse in expertise and perspectives with a focus on collaboration and innovation. Our teams are at the frontier of the Nation's most complex and rewarding challenges. Join our team.

Barbaricum is seeking an Scientist III to directly support the anticipated Naval Surface Warfare Center (NSWC) Crane Division, Model Based Engineering Assessment Division (Code MXM), under Solicitation N00164-26-R-0017. Code MXM's mission is mission engineering analysis and assessment of complex Naval, DoD, and joint kill chains — with a specialized focus on Electromagnetic Spectrum Operations (EMSO) enabled analysis. As a Scientist III, you will construct, modify, and perform statistical and analytical investigations with mathematical and computer simulation models in support of EMSO. You will provide research and development support in state-of-the-art computational electromagnetic (EM) modeling, atmospheric modeling, swarming algorithms, and data/signal processing, and will bring machine learning and advanced data analytics to bear on mission engineering questions. This role is the scientific engine behind Code MXM's modeling, simulation, and operations research work.

KEY RESPONSIBILITIES

  • Construct, modify, and perform statistical/analytical investigations with mathematical/computer simulation models supporting EMSO (SOW 4.6.3).
  • Provide R&D support defining and using state-of-the-art approaches for computational EM modeling, atmospheric modeling, swarming algorithms, and data/signal processing.
  • Research state-of-the-art tool sets to support modeling, simulation, and statistical/analytical investigations.
  • Conduct academic and industry technical reviews and perform model and algorithm development.
  • Apply machine learning and other data-analytic approaches to analytics objectives (CDRLs A010, A011, A024, A025).

REQUIRED QUALIFICATIONS

  • Active DoD SECRET clearance (minimum); U.S. citizenship required.
  • Bachelor's degree from an ABET-accredited institution.
  • 10+ years of experience in a Life or Physical Science discipline.
  • Ability to construct, modify, and perform statistical/analytical investigations with mathematical/computer simulation models, including computational EM modeling.

DESIRED QUALIFICATIONS

  • Active TS/SCI clearance (preferred).
  • Master's or Doctorate degree.
  • Experience with computational EM tools, atmospheric propagation modeling (ITU-R, TIREM), and Python-based analytics.
  • Applied machine learning / data-mining experience against large signal datasets.
  • Prior EMSO / electronic warfare / Navy operations research experience.

EEO Commitment

All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law.

Skills

PythonMachine Learning