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Model Predictive Control Phd Jobs (NOW HIRING)

Avride

C++ Software Engineer - Control

Austin, TX

In this role, you will architect sophisticated control systems using Model Predictive Control (MPC) and identify the dynamic parameters of our vehicles. What You'll Do * Design, implement, and ...

Corning

Sr. Engineer, Advanced Process Controls

Painted Post, NY · On-site

$82.20K - $108.50K/yr

... model predictive control (MPC), and large-scale numerical optimization for production planning ... S. or PhD in Electrical, Mechanical, or Chemical Engineering (or a related field) with coursework ...

Corning

Sr. Engineer, Advanced Process Controls

Painted Post, NY · On-site

$82.20K - $108.50K/yr

... model predictive control (MPC), and large-scale numerical optimization for production planning ... S. or PhD in Electrical, Mechanical, or Chemical Engineering (or a related field) with coursework ...

Optimal Inc.

Robotics System Developer

Warren, MI · On-site

Experience with model predictive control is a plus. Ideal Candidate Profile The ideal candidate is a well-rounded robotics engineer who can combine software, sensing, controls, and robot integration ...

Avride

C++ Software Engineer - Control

Austin, TX · On-site

In this role, you will architect sophisticated control systems using Model Predictive Control (MPC) and identify the dynamic parameters of our vehicles. What You'll Do * Design, implement, and ...

Instacart

OR · On-site

MS or PhD in operations research, applied mathematics, control systems, computational economics, or ... Experience with adaptive control or model-predictive control in production systems. * Familiarity ...

Optimal Inc.

Robotics System Developer

Warren, MI · On-site

Experience with model predictive control is a plus. Ideal Candidate Profile The ideal candidate is a well-rounded robotics engineer who can combine software, sensing, controls, and robot integration ...

SpaceX

GNC Engineer, Orbit Control (Starlink)

Redmond, WA · On-site

$145K - $175K/yr

Master's degree or PhD in a field relevant to this position * Expertise in orbital mechanics ... Prior exposure to trajectory optimization, model predictive control, convex optimization, and mixed ...

Sanofi

Senior Scientist - Process Modelling

Framingham, MA · On-site

$94.10K - $128.60K/yr

PhD in Chemical Engineering, Biochemical Engineering, Process Systems Engineering, Bioengineering ... model predictive control * Track record of peer-reviewed publications in process modeling ...

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Model Predictive Control Phd information

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How much do model predictive control phd jobs pay per year?

As of Jun 3, 2026, the average yearly pay for model predictive control phd in the United States is $96,574.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,500.00 and $108,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Model Predictive Control PhD, and why are they important?

To thrive as a Model Predictive Control (MPC) PhD, you need advanced knowledge in control theory, optimization, and applied mathematics, typically supported by a doctoral degree in engineering or a related field. Expertise in simulation software (like MATLAB/Simulink), programming languages (such as Python or C++), and familiarity with real-time control systems is essential. Strong analytical thinking, problem-solving, and effective communication skills help distinguish top candidates in both academic and industry settings. Mastery of these technical and soft skills ensures the ability to develop, implement, and communicate sophisticated control solutions for complex, real-world systems.

What are the typical research and collaboration opportunities available to a Model Predictive Control PhD candidate during their studies?

As a Model Predictive Control PhD candidate, you will often collaborate with multidisciplinary teams, including faculty advisors, postdoctoral researchers, and industry partners. Research opportunities may include working on advanced control algorithms for real-world systems such as robotics, automotive, or energy applications. Many programs encourage publishing in peer-reviewed journals and presenting at conferences, which helps build your professional network. Additionally, you may have the chance to contribute to grant-funded projects, mentor undergraduate students, and participate in workshops or internships related to control systems.

What is a Model Predictive Control (MPC) PhD?

A Model Predictive Control (MPC) PhD is a doctoral program focused on advanced research in model predictive control, a type of control algorithm extensively used in engineering, robotics, and process industries. Students in this program typically develop new theories, algorithms, or applications for MPC, contributing to areas such as optimization, real-time systems, or autonomous systems. The program involves substantial coursework, original research, and the completion of a dissertation under faculty supervision. Graduates are prepared for careers in academia, industry research, or advanced engineering roles.

What is the difference between Model Predictive Control Phd vs Control Systems Engineer?

AspectModel Predictive Control PhdControl Systems Engineer
Required CredentialsPhD in Control Engineering or related fieldBachelor's or Master's in Engineering or related field
Work EnvironmentResearch, academia, or R&D departmentsIndustry, manufacturing, or automation sectors
Industry UsageDeveloping advanced control algorithms, research projectsImplementing control solutions, system design

The Model Predictive Control Phd typically focuses on research and development of advanced control algorithms, often in academic or R&D settings, requiring a PhD. Control Systems Engineers work in industry, applying control principles to real-world systems, often with a bachelor's or master's degree. Both roles involve control theory but differ in scope, environment, and experience level.

Infographic showing various Model Predictive Control Phd job openings in the United States as of May 2026, with employment types broken down into 10% Internship, 85% Full Time, and 5% Contract. Highlights an 85% In-person, 5% Hybrid, and 10% Remote job distribution, with an average salary of $96,574 per year, or $46.4 per hour.

C++ Software Engineer - Control

Avride

Austin, TX

Other

Posted 10 days ago

Job description

About the Team

Avride is a fast-growing leader in the autonomous vehicle and delivery robot industry. We are building the future of mobility from the ground up, backed by a core team with over seven years of pioneering experience in autonomous technology.

Our Control team is the driving force behind our vehicle's precision. We design robust systems that navigate trajectories with centimeter-level accuracy-smoother and more reliably than a human driver-across a vast range of real-world conditions.

About the Role

We are seeking a highly skilled software engineer to advance Avride's core Control System. In this role, you will architect sophisticated control systems using Model Predictive Control (MPC) and identify the dynamic parameters of our vehicles.

What You'll Do
  • Design, implement, and optimize cutting-edge control systems in modern C++ (C++17/20).
  • Develop and refine robust, high-precision solutions for trajectory tracking.
  • Analyze and iterate on system performance using real-world vehicle data.
  • Collaborate closely with engineers from our Planning and Hardware teams to build a cohesive and reliable self-driving system.
  • Write clean, maintainable, and optimized production-quality code.
  • Profile and optimize algorithms to meet real-time performance constraints.
What You'll Need
  • 3+ years of professional software engineering experience.
  • Expertise in modern C++.
  • Deep understanding of algorithms, data structures, and software design patterns.
  • Hands on experience on data analysis and basic statistical methods.
  • Exceptional communication and collaboration skills, with a focus on delivering results and driving projects to completion.
Nice to Have
  • Direct experience in robotics, with a strong grasp of Optimization, MPC, and system dynamics.
  • Digital signal processing techniques to analyse real-word sensor data.
  • Advanced knowledge of mathematics (optimization, probability, mechanics) and a proven ability to translate complex theories into production-ready algorithms.
  • Relevant publications or achievements in hackathons and programming contests.
  • A passion for staying at the forefront of the field, actively seeking and implementing state-of-the-art ideas to push our performance beyond the current horizon.

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