Analytics-Driven Systems Modeling Engineer

Johns Hopkins Applied Physics Laboratory; Laurel (MD); Hybrid; USD 100,000 - 245,000; Full time

Job summary

Johns Hopkins Applied Physics Laboratory seeks a Systems Engineer (Systems Modeling & Performance Analyst) to validate system resilience and verify performance across national defense missions. You will work within the System Realization and Resilience Group to translate physics-based and statistical models into digital engineering results.

You will interact with Cameo/MagicDraw environments to map proofs and verification criteria to the architecture, supporting design margins evaluation and

Qualifications

• BS in Physics, Applied Mathematics, or an engineering discipline with focus on mathematical modeling and experimental data analysis.
• 2+ years of quantitative data analysis, physics-based simulations, or test data reduction.
• Knowledge of MBSE tools such as Cameo/MagicDraw and verification concepts.

Responsibilities

• Interpret and integrate physics-based and statistical models within a digital engineering framework to analyze complex system behaviors and reduce empirical data.
• Analyze designs and experimental/test data to identify design risks and uncertainties in model representations.
• Perform analytical trade studies and sensitivity assessments for environmental variations and component degradation.
• Interface with digital engineering environments, mapping proofs and criteria to system architecture using Cameo/MagicDraw.

Skills

Quantitative analysis

Statistical evaluation

Modeling & verification

SysML & MBSE

Data interpretation

Security clearance

Education

Bachelor's degree in Physics / Applied Math / Engineering

Tools

Cameo Enterprise Architect

MagicDraw

Job description

Johns Hopkins Applied Physics Laboratory seeks a Systems Engineer (Systems Modeling & Performance Analyst) to validate system resilience and verify performance across national defense missions. You will work within the System Realization and Resilience Group to translate physics-based and statistical models into digital engineering results.

You will interact with Cameo/MagicDraw environments to map proofs and verification criteria to the architecture, supporting design margins evaluation and