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Internship Control Theory Engineer Jobs in Texas

Engineering / R&D Employment Type: Full-time Reports To: Director of Robotics or Engineering ... Solid understanding of kinematics, dynamics, control theory, and path planning. * Practical ...

Control System Engineer

Dallas, TX · On-site

$90K - $100K/yr

Stay informed on the latest developments in control systems theories, techniques, and technologies. Education and Experience Requirements: BS Degree in Electrical Engineering from an ABET-accredited ...

Control System Engineer

Dallas, TX · On-site

$90K - $100K/yr

Stay informed on the latest developments in control systems theories, techniques, and technologies. Education and Experience Requirements: BS Degree in Electrical Engineering from an ABET-accredited ...

The Job Guidance, Navigation, and Control Engineers leverage their knowledge of dynamics, control theory, and software development to control the attitude and trajectory of an array of space vehicles.

Showing results 21-40

Internship Control Theory Engineer information

What is the difference between Internship Control Theory Engineer vs Control Systems Engineer?

AspectInternship Control Theory EngineerControl Systems Engineer
CredentialsTypically pursuing or recent graduate in control engineering, electrical engineering, or related fieldsBachelor's or master's degree in control engineering, electrical engineering, or related fields
Work EnvironmentInternship setting, often in research labs or development teamsFull-time professional role in industry, manufacturing, or technology companies
Industry UsageUsed for training, skill development, and project support during studiesDesign, implementation, and maintenance of control systems in real-world applications

In summary, an Internship Control Theory Engineer is a temporary, learning-focused role for students or recent graduates, while a Control Systems Engineer is a full-time professional responsible for designing and managing control systems in industry.

What types of projects can an internship control theory engineer expect to work on, and how is mentorship typically provided?

As an Internship Control Theory Engineer, you can expect to work on projects involving modeling, simulation, and analysis of dynamic systems—often supporting the development or improvement of control algorithms for mechanical, electrical, or robotic systems. Interns frequently assist with data analysis, running simulations in tools like MATLAB/Simulink, and performing hardware-in-the-loop testing. Mentorship is commonly provided through regular check-ins with a senior engineer or supervisor, collaborative team meetings, and hands-on guidance during project tasks. This supportive environment helps interns quickly build technical skills and gain exposure to real-world engineering workflows.

What does an internship control theory engineer do?

An Internship Control Theory Engineer works alongside experienced engineers to design, analyze, and implement control systems for various applications, such as robotics, automation, or aerospace. Interns typically assist in modeling dynamic systems, developing algorithms, running simulations, and supporting experimental validation. This role offers hands-on experience with industry tools and exposure to real-world engineering challenges while applying theoretical knowledge from coursework.

What are the key skills and qualifications needed to thrive as an internship control theory engineer?

To thrive as an Internship Control Theory Engineer, a solid background in mathematics, dynamics, and control systems, typically supported by coursework in engineering or applied mathematics, is essential. Familiarity with simulation tools like MATLAB/Simulink and programming languages such as Python or C++ is commonly expected. Strong problem-solving abilities, curiosity, and effective communication help interns collaborate and learn quickly in technical environments. These skills and qualities enable efficient analysis, design, and implementation of control solutions, contributing to successful project outcomes.
What cities in Texas are hiring for Internship Control Theory Engineer jobs? Cities in Texas with the most Internship Control Theory Engineer job openings:
Infographic showing various Internship Control Theory Engineer job openings in Texas as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Controls & Modeling Engineer (Senior - Principal) - Advanced Automation

Halliburton

Houston, TX • On-site, Remote

$83K - $110K/yr

Other

Re-posted 17 days ago


Halliburton rating

7.2

Company rating: 7.2 out of 10

Based on 133 frontline employees who took The Breakroom Quiz

335th of 441 rated engineering


Job description

We are looking for the right people - people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the world's largest providers of products and services to the global energy industry.

About Sperry Drilling

Sperry Drilling delivers industry-leading Measurement-While-Drilling (MWD), Logging-While-Drilling (LWD), and Rotary Steerable System (RSS) technologies that help operators drill safer, faster, and more precisely. Through advanced downhole tools, real-time data acquisition, and reliability-driven engineering, Sperry enables customers to maximize well placement, efficiency, and reservoir understanding in every drilling environment.

About the Role

The Controls & Modeling Engineer advances research and development of next-generation automation, controls, robotics, and intelligent systems technologies within the Advanced Controls COE.

This role focus on rigorous application of advanced control theory, dynamic modeling, estimation, optimization, machine learning, and agentic AI to high-value engineering problems.

Work spans early-stage concept generation, algorithm development, simulation and validation, prototype implementation, and transition of emerging technologies into deployable workflows and systems.

This position contributes to strategic R&D initiatives with direct commercial relevance. Scope includes development of physics-based and data-driven methods for automation, operational decision support, autonomous and semi-autonomous systems, and model-based performance improvement. Close collaboration with multidisciplinary teams across engineering, software, digital, and operations.


Key Responsibilities

  • Develop and evaluate agentic AI systems that combine reasoning, tools, data, and simulation assets to enable advanced technical analysis, automation, and human-in-the-loop decision making. 
  • Integrate large language models (LLMs), retrieval-augmented systems, and AI agents with controls, modeling, and optimization frameworks. 
  • Develop machine learning, data analytics, and hybrid physics-AI approaches to improve system performance, automation, and operational efficiency. 
  • Develop software tools, workflows, orchestration pipelines, and visualization capabilities to support AI-enabled engineering and operations. 
  • Conduct research and development in advanced controls, robotics, dynamic modeling, and automation for complex engineering systems. 
  • Design & apply advanced control techniques including adaptive, nonlinear, robust, optimal, and model predictive control (MPC). 
  • Develop and validate dynamic models, simulations, and system identification methodologies. 
  • Collaborate with multidisciplinary teams across engineering, software, data science, and operations. 
  • Contribute to technical innovation through patents, publications, conferences, and internal programs. 
Qualifications

Required

  • PhD or equivalent experience in a relevant engineering or scientific discipline with emphasis on controls, dynamic systems, automation, machine learning, or intelligent systems; or equivalent R&D experience. 
  • Experience with agentic AI, LLM-based workflows, orchestration frameworks, or tool-using AI agents applied to scientific, industrial, or engineering use cases. 
  • Deep knowledge of control theory, including modern control, optimal control, Model Predictive Control (MPC), and system dynamics. 
  • Knowledge of robotics, mechatronics, highDoF systems, path planning, and dynamic modeling. 
  • Strong technical communication and collaboration skills. 

Preferred

  • Ability to build data pipelines, workflows, and analytical tools for AI/ML tool chain which includes data cleaning, feature extraction, optimization, and insight generation. 
  • Strong programming skills in MATLAB, Python, C/C++, C#, Java, or similar languages. 
  • Create dashboards and use data visualization tools such as Python, or JavaScript Typescript frameworks. 
  • Ability to design, analyze, and troubleshoot control systems, sensors, actuators, pumps, VFDs, and automation hardware. 
  • Strong capability to read and interpret electrical schematics, mechanical drawings, P&IDs, flow charts, and causeandeffect diagrams.  

Candidates exceeding minimum requirements may be considered for higher-level positions based on experience, additional qualifications, and business needs. Career progression ranges Controls & Modeling Engineer Senior to Controls & Modeling Engineer Principal. 

World Class Benefits

At Halliburton, we're committed to supporting you and your family with a comprehensive and affordable benefits package that covers your physical, emotional, financial, and parental needs - now and in the future. When you join our team, you'll gain access to a wide range of programs designed to help you thrive at work and at home.

Click here to review a summary of the benefits available once you join.

Core Competencies

Advanced Control Systems | Control Theory & System Identification | Robotics & Autonomous Systems | High DoF Systems & Path Planning | Modeling & Simulation | Control + Machine Learning | Data Analytics + Engineering | Neural Networks & Bayesian Methods | MATLAB/Simulink & Python | Dynamic Systems & Optimization | Robotics + Control | Theory + Practical Deployment | Field Implementation Experience | Cross-Functional Collaboration | Innovation & Technology Development

Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.

Location

3000 N. Sam Houston Parkway E., Houston, Texas, 77032, United States

Job Details

Requisition Number: 207457  
Experience Level: Experienced Hire 
Job Family: Engineering/Science/Technology 
Product Service Line: Sperry Drilling Svcs   
Full Time / Part Time: Full Time

Additional Locations for this position: 

Compensation Information
Compensation is competitive and commensurate with experience.


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About Halliburton

Sourced by ZipRecruiter

Halliburton, headquartered in Houston, TX, US, is a world-renowned corporation in the oilfield services industry. Established in 1919, the company has made significant inroads in the energy sector, playing a pivotal role in oil and gas explorations across the globe. One can visit their official website, halliburton.com, to learn more about their business operations, products, and services. Halliburton specializes in a broad spectrum of services including locating hydrocarbons, managing geological data, drilling and formation evaluation, well construction and completion, and optimizing production throughout the life of the field. Halliburton’s mission is to maximize the value of oil and gas assets.

Industry

Health care and social assistance

Company size

10,000+ Employees

Headquarters location

Houston, TX, US