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Physics Ai Simulation Jobs in Alabama (NOW HIRING)

AI Engineer

Huntsville, AL ยท On-site

$99K - $225K/yr

You Have: * 3+ years of experience develop ing and maintaining multi physics simulation models * Experience designing and implementing intelligent AI agent architectures * Experience building ...

AI Engineer

Huntsville, AL ยท On-site

$99K - $225K/yr

You Have: * 3+ years of experience developing and maintaining multi physics simulation models * Experience designing and implementing intelligent AI agent architectures * Experience building ...

AI Engineer

Huntsville, AL ยท On-site

$99K - $225K/yr

You Have: * 3+ years of experience developing and maintaining multi physics simulation models * Experience designing and implementing intelligent AI agent architectures * Experience building ...

AI Engineer

Huntsville, AL ยท On-site +1

$99K - $225K/yr

You Have: * 3+ years of experience developing and maintaining multi physics simulation models * Experience designing and implementing intelligent AI agent architectures * Experience building ...

Bachelor's Degree or higher in Mathematics, Computer Science, Computer Engineering, Physics, Data ... Familiarity with structured data analysis, simulations, or scientific computing environments.

Showing results 41-60

Physics Ai Simulation information

What is a Physics AI Simulation?

A Physics AI Simulation job involves creating, developing, and maintaining computer simulations that model physical systems using artificial intelligence techniques. Professionals in this field use their expertise in physics, mathematics, and programming to design simulations for research, engineering, gaming, or educational purposes. They often work with machine learning algorithms to improve the accuracy and efficiency of these simulations, enabling better predictions and deeper insights into complex phenomena. This role typically requires strong analytical skills and experience with simulation software and programming languages.

What are the key skills and qualifications needed to thrive as a Physics AI Simulation specialist?

To thrive as a Physics AI Simulation Specialist, you need a solid background in physics, mathematics, and computer science, often supported by a relevant degree or advanced studies. Familiarity with simulation software such as MATLAB, Simulink, or Unity, and programming languages like Python or C++, is typically required, along with experience in machine learning frameworks. Strong problem-solving, analytical thinking, and effective collaboration skills help distinguish top performers in this field. These competencies ensure accurate modeling, innovative solutions, and effective teamwork in developing realistic and efficient AI-driven simulations.

How do professionals in Physics AI Simulation typically collaborate with other teams to develop accurate models?

In Physics AI Simulation roles, collaboration is integral to creating reliable simulation models. Professionals often work closely with domain experts, such as physicists and engineers, to validate the scientific accuracy of their AI-driven simulations. They also partner with software developers to integrate simulation tools into broader platforms and may engage with data scientists to refine algorithms using experimental or real-world data. Regular interdisciplinary meetings and code reviews are common practices to ensure alignment and quality throughout the project lifecycle.

What is the difference between Physics Ai Simulation vs Data Scientist?

AspectPhysics Ai SimulationData Scientist
Required CredentialsPhysics or Computer Science degree, knowledge of AI and simulation toolsStatistics, Mathematics, Computer Science degree, programming skills
Work EnvironmentResearch labs, tech companies, simulation software developmentBusiness, tech firms, data analysis teams
Industry UsagePhysics research, AI-driven simulations, scientific modelingData analysis, predictive modeling, business insights

Physics Ai Simulation focuses on creating AI-driven models to simulate physical phenomena, often requiring physics and AI expertise. Data Scientists analyze data to extract insights, build predictive models, and support decision-making. While both roles involve data and AI, Physics Ai Simulation emphasizes physical modeling and simulation, whereas Data Scientists focus on data analysis and interpretation.

What are popular job titles related to Physics Ai Simulation jobs in Alabama?

For Physics Ai Simulation jobs in Alabama, the most frequently searched job titles are:

What cities in Alabama are hiring for Physics Ai Simulation jobs?

Cities in Alabama with the most Physics Ai Simulation job openings:

RF/Radar Engineer - Mid Level

Phased n Research, Inc.

Huntsville, AL โ€ข On-site

Full-time

Posted 21 days ago


Job description

RF/Radar Engineer – Mid LevelLocation: Huntsville, AL; Denver, COClearance: Active Top Secret/SCIPosition Type: Full-TimeAbout the RolePhased n Research is seeking multiple mid-level RF/Radar Engineers to support radar engineering analysis and production of technically defensible threat-system parametrics for U.S. Air Force intelligence and mission-planning applications. The engineers will perform radar analysis, physics-based modeling, engineering derivation, and technical validation while helping translate proven radar engineering methods into repeatable, AI-assisted analytic workflows.You will work with senior engineers, intelligence analysts, and software developers on physics-based radar modeling and simulation (M&S), engineering analysis, algorithm application and validation, and automated analytic workflows. You will apply radar engineering methods to accelerate threat-data production while ensuring calculated and automated results remain grounded in source information, established engineering methods, and technically defensible analysis.Radar Engineering & Analysis ResponsibilitiesPerform radar engineering analysis to characterize foreign radar systems, operating modes, and mission-planning threat parameters in support of threat-data package production.Analyze and derive radar parameters including transmitter power, antenna characteristics, receiver sensitivity, detection range, waveform and PRI/PRF characteristics, Doppler and velocity performance, integration gain, scan behavior, and related system performance.Apply established radar equations, signal-processing relationships, antenna theory, electromagnetic principles, and physics-based models to calculate or assess parameters when source information is incomplete, inconsistent, or indirect.Research, interpret, and reconcile technical information from intelligence reports, measurements, drawings, schematics, databases, and other approved sources to support manual and AI-assisted threat-data production.Perform radar modeling, simulation, and reference calculations to assess detection, SNR, waveform, antenna, signal-processing, and mode-specific radar performance.Document source provenance, engineering assumptions, calculations, uncertainty, confidence, and technical rationale supporting calculated or assessed values.Perform technical checks and cross-parameter consistency assessments; identify incomplete, inconsistent, or unsupported results and recommend cases requiring senior SME adjudication.Support technical validation of calculated, modeled, and automated radar parameters against approved engineering methods, reference results, and expected physical behavior.Modeling, Simulation & Engineering Method Development ResponsibilitiesOperate radar modeling, simulation, and analysis tools to characterize radar performance and derive required threat parameters.Develop and execute MATLAB and/or Python calculations and scripts supporting radar performance, antenna, receiver, waveform, signal-processing, and related parametric analysis.Apply established algorithms and physics-based models to generate engineering assessments, reference calculations, and test cases supporting threat-data production and automated engineering workflows.Compare modeled and calculated results against available source data, reported performance, and approved reference cases; investigate discrepancies and elevate significant fidelity or consistency issues to senior engineers. Support testing and validation of radar algorithms and engineering workflows by executing representative cases, evaluating results against established tolerances, and documenting findings.AI-Assisted Analytic Workflow ResponsibilitiesSupport translation of approved radar engineering methods, calculations, parameter relationships, and consistency checks into repeatable automated engineering playbooks and analytic workflows.Develop and execute engineering reference cases, expected results, and test data under approved engineering methods to verify automated radar-analysis workflows.Evaluate AI-generated radar parameters and assessments against source information, approved engineering methods, physics-based calculations, cross-parameter relationships, and established acceptance tolerances.Identify and document unsupported, inconsistent, or anomalous automated results; investigate likely causes and elevate significant discrepancies for senior technical disposition.Support regression testing of automated engineering workflows and radar algorithms following implementation changes, method updates, or identified discrepancies.Collaboration & Program Execution ResponsibilitiesDevelop and maintain engineering documentation, analysis records, model descriptions, reference calculations, test results, and other technical artifacts supporting program deliverables and Government reviews.Prepare and contribute to technical briefings, analysis results, and engineering recommendations for U.S. Air Force stakeholders.Participate in technical interchange meetings (TIMs), engineering reviews, and program working groups as required. Collaborate with radar engineers, intelligence analysts, and software/AI developers to resolve technical issues and ensure approved engineering methods are accurately represented in implemented workflows.Work with senior radar SMEs on complex or novel technical assessments and support resolution of technical issues affecting threat-data production and validation.·Position RequirementsBachelor's degree in Electrical Engineering, Computer Engineering, Physics, or a closely related technical discipline with 5+ years of relevant experience; a relevant advanced degree may substitute for a portion of the experience requirement.Demonstrated foundation in radar engineering or radar-system analysis, with experience in one or more related areas such as RF engineering, electromagnetics, digital signal processing, or modeling and simulation.Experience applying engineering principles and physics-based analytical methods to radar, RF, or related system-performance problems.Experience using MATLAB and/or Python for engineering analysis, modeling, simulation, or data analysis.Ability to independently perform assigned technical analyses, document assumptions and results, and recognize issues requiring senior technical review.Ability to communicate technical concepts and analysis results clearly in written and verbal formats.Active Top Secret/SCI clearance required.Preferred QualificationsExperience with radar performance analysis, including detection, transmitter/receiver characteristics, antenna performance, waveform/PRI/PRF characteristics, Doppler processing, integration, scanning, or related radar parameters.Experience with radar modeling and simulation, signal processing, antennas, electromagnetics, electronic warfare, or threat-system characterization.Experience applying physics-based methods to characterize radar or RF system performance from incomplete, indirect, or conflicting technical information.Experience supporting technical intelligence, foreign radar analysis, or DoD/Intelligence Community missions.Familiarity with, or experience applying, ICD 203 and ICD 206 principles to analytic tradecraft and technical intelligence production.Familiarity with CSDB, EWIRDB, JMPS, TERF, USELMS, or related threat-parametric or mission-planning workflows.Experience developing or validating engineering models, reference calculations, test cases, acceptance criteria, or regression tests.Familiarity with AI/ML-assisted engineering, automated analytic workflows, or validation of AI-generated technical results.