Job Requirements
Washington, DC
Public Trust Polygraph not specified
Early Career (2+ yrs experience)
$110,000 - $120,000
Job Description
Purpose and Impact: (a write up about the program that will attract candidates)
We are seeking a highly adaptable and self-directed Signal Processing Scientist to join our dynamic research and development team. This role is designed for a creative, practical problem-solver who thrives on breadth and variety, rather than being confined to a single narrow project.
In this role, you will bridge the gap between advanced academic research and real-world operational impact. You will leverage your creative instincts and deep technical expertise to translate complex mathematical models—specifically in universal spectral estimation and array processing—into efficient, testable code applied to CUI and classified datasets. We offer a highly collaborative environment that values innovative approaches, rapid prototyping, and autonomy to critically evaluate and dictate technical solutions.
Work Schedule: M – F 8 AM – 5 PM EST
Essential Responsibilities: (describe the day-to-day)
• Acoustic Modeling & Prediction: Utilize numerical acoustic propagation models to generate statistical predictions of transmission loss and ambient sound in realistic Arctic environments.
• Data Integration & Analysis: Incorporate complex environmental datasets—including satellite observations, oceanographic forecasts, and field observations—into numerical simulations to ensure accurate real-world modeling.
• Model Validation: Test and validate physical models for transmission loss and ambient sound predictions against empirical acoustic recordings gathered in under-ice environments.
• Field Operations & Logistics: Support experimental preparation and on-ice Arctic field work. This encompasses testing observing equipment in a laboratory setting, assisting with experiment planning, and managing field logistics.
• Scientific Communication: Author technical reports, document experimental methodologies, and present complex scientific findings clearly to internal teams and external stakeholders.
• Travel & Deployment: Participate in occasional field travel to collect data in Arctic environments (travel is not expected to exceed 3–4 weeks per year).
Work Environment, Physical Demands, and Mental Demands: Field work is required.
Minimum Requirements (Knowledge, Skills, and Abilities):
I. Knowledge
• Scientific Programming: Extensive experience utilizing programming languages such as Fortran, C++, Python, or Matlab for modeling and data analysis.
• Numerical Simulations: Deep understanding of numerical simulations and mathematical methods applied to wave propagation.
• Observational Equipment: Familiarity with the mechanics, deployment, and operation of acoustics and/or ocean science observing equipment.
• Signal Processing: Strong foundational knowledge in signal processing techniques as applied to experimental physics or oceanography.
II. Skills
• Experimental Data Analysis: Proven skill in reducing, processing, and analyzing complex, noisy datasets (e.g., under-ice acoustic recordings) to extract actionable scientific insights.
• Technical Writing: Strong scientific writing skills, with the ability to document algorithms, physical models, and field results clearly for both peer-reviewed and operational audiences.
• Equipment Troubleshooting: Hands-on capability to set up, calibrate, and troubleshoot sensitive observational equipment in a lab environment prior to field deployment.
III. Abilities
• Adaptability & Field Readiness: Ability to successfully operate and collect data in remote, harsh, or austere environments (specifically Arctic on-ice conditions) for short durations (3-4 weeks/year).
• Autonomy & Initiative: Self-directed and capable of driving both computational and logistical tasks forward with minimal supervision.
• Collaboration: Ability to work seamlessly across multidisciplinary teams, bridging the gap between theoretical modelers and physical field operators.
• Precision: Highly detail-oriented, ensuring rigorous accuracy in both numerical code execution and physical equipment calibration.
Security Clearance Required: Will need to start once security paperwork is in the DOW database and the SF86 has been verified.
• Minimum Education: Education: Degree in Oceanography, Physics, Acoustics, Engineering, Applied Mathematics, or a closely related scientific discipline. (Specify required degree level here, e.g., M.S. or Ph.D., or B.S. with equivalent experience).
• Domain Experience: Demonstrated applied experience in experimental data analysis, wave propagation simulations, and acoustics.
• Unique Backgrounds: Candidates who possess a blend of rigorous computational modeling experience combined with practical, hands-on mechanical troubleshooting or field-expedition experience are highly encouraged to apply.
Minimum Years of Experience: 0-2 Phd, 2-4, Masters, 3-5 BS.
Required Certifications: N/A
Preferred Qualifications: AI if applicable to your program
We are seeking a highly adaptable and self-directed Signal Processing Scientist to join our dynamic research and development team. This role is designed for a creative, practical problem-solver who thrives on breadth and variety, rather than being confined to a single narrow project.
In this role, you will bridge the gap between advanced academic research and real-world operational impact. You will leverage your creative instincts and deep technical expertise to translate complex mathematical models—specifically in universal spectral estimation and array processing—into efficient, testable code applied to CUI and classified datasets. We offer a highly collaborative environment that values innovative approaches, rapid prototyping, and autonomy to critically evaluate and dictate technical solutions.
Work Schedule: M – F 8 AM – 5 PM EST
Essential Responsibilities: (describe the day-to-day)
• Acoustic Modeling & Prediction: Utilize numerical acoustic propagation models to generate statistical predictions of transmission loss and ambient sound in realistic Arctic environments.
• Data Integration & Analysis: Incorporate complex environmental datasets—including satellite observations, oceanographic forecasts, and field observations—into numerical simulations to ensure accurate real-world modeling.
• Model Validation: Test and validate physical models for transmission loss and ambient sound predictions against empirical acoustic recordings gathered in under-ice environments.
• Field Operations & Logistics: Support experimental preparation and on-ice Arctic field work. This encompasses testing observing equipment in a laboratory setting, assisting with experiment planning, and managing field logistics.
• Scientific Communication: Author technical reports, document experimental methodologies, and present complex scientific findings clearly to internal teams and external stakeholders.
• Travel & Deployment: Participate in occasional field travel to collect data in Arctic environments (travel is not expected to exceed 3–4 weeks per year).
Work Environment, Physical Demands, and Mental Demands: Field work is required.
Minimum Requirements (Knowledge, Skills, and Abilities):
I. Knowledge
• Scientific Programming: Extensive experience utilizing programming languages such as Fortran, C++, Python, or Matlab for modeling and data analysis.
• Numerical Simulations: Deep understanding of numerical simulations and mathematical methods applied to wave propagation.
• Observational Equipment: Familiarity with the mechanics, deployment, and operation of acoustics and/or ocean science observing equipment.
• Signal Processing: Strong foundational knowledge in signal processing techniques as applied to experimental physics or oceanography.
II. Skills
• Experimental Data Analysis: Proven skill in reducing, processing, and analyzing complex, noisy datasets (e.g., under-ice acoustic recordings) to extract actionable scientific insights.
• Technical Writing: Strong scientific writing skills, with the ability to document algorithms, physical models, and field results clearly for both peer-reviewed and operational audiences.
• Equipment Troubleshooting: Hands-on capability to set up, calibrate, and troubleshoot sensitive observational equipment in a lab environment prior to field deployment.
III. Abilities
• Adaptability & Field Readiness: Ability to successfully operate and collect data in remote, harsh, or austere environments (specifically Arctic on-ice conditions) for short durations (3-4 weeks/year).
• Autonomy & Initiative: Self-directed and capable of driving both computational and logistical tasks forward with minimal supervision.
• Collaboration: Ability to work seamlessly across multidisciplinary teams, bridging the gap between theoretical modelers and physical field operators.
• Precision: Highly detail-oriented, ensuring rigorous accuracy in both numerical code execution and physical equipment calibration.
Security Clearance Required: Will need to start once security paperwork is in the DOW database and the SF86 has been verified.
• Minimum Education: Education: Degree in Oceanography, Physics, Acoustics, Engineering, Applied Mathematics, or a closely related scientific discipline. (Specify required degree level here, e.g., M.S. or Ph.D., or B.S. with equivalent experience).
• Domain Experience: Demonstrated applied experience in experimental data analysis, wave propagation simulations, and acoustics.
• Unique Backgrounds: Candidates who possess a blend of rigorous computational modeling experience combined with practical, hands-on mechanical troubleshooting or field-expedition experience are highly encouraged to apply.
Minimum Years of Experience: 0-2 Phd, 2-4, Masters, 3-5 BS.
Required Certifications: N/A
Preferred Qualifications: AI if applicable to your program
group id: 91156626
