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Model Predictive Control Jobs in Oregon (NOW HIRING)

We uniquely pair traditional energy storage with predictive load control technology to ... Research and model site economics, operating strategies, and enrollment procedures for demand ...

Establish and govern a common maintenance operating model, including work identification, planning and scheduling, preventive and predictive maintenance, outage management, backlog control, equipment ...

Strong understanding of lakehouse, medallion, data warehouse, and data modeling patterns, including ... control, documentation, and observability. * Experience preparing enterprise data for AI-enabled ...

... control, and predictive monitoring. Characterize and optimize optical subsystems, including ... Experience in optical modeling, thin-film optics, image processing, computer vision, signal ...

Build and productionize predictive models (e.g., LTV, churn/propensity, audience response, budget ... version control (Git). * Demonstrated ability to translate ambiguous business questions into ...

Data Scientist/Statistician

Hillsboro, OR · On-site

$116K - $228K/yr

Drives organization to use process control systems to improve capability, matching, and stability of semiconductor process technologies * Use predictive modeling, statistics, Machine Learning, Data ...

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Showing results 21-40

Model Predictive Control information

What is model predictive control?

Model Predictive Control (MPC) is an advanced method of process control that uses a mathematical model to predict and optimize the future behavior of a system. It works by solving an optimization problem at each control step to determine the best sequence of control actions, taking into account system constraints and objectives. MPC is widely used in industries such as chemical processing, energy, and automotive because it can handle multivariable control problems and anticipate future events. Its predictive nature allows for improved performance, stability, and efficiency compared to traditional control methods.

What are the typical challenges faced by engineers working with model predictive control systems in an industrial setting?

Engineers working with Model Predictive Control systems often encounter challenges related to model accuracy, computational demands, and real-time implementation. Ensuring the process model accurately represents the plant dynamics is critical, as discrepancies can lead to suboptimal control performance. Additionally, MPC algorithms can be computationally intensive, particularly for large-scale or fast processes, requiring careful tuning and optimization to maintain real-time operation. Collaboration with process engineers and IT specialists is common, as integrating MPC with existing control systems and plant infrastructure is a key part of the role.

What are the key skills and qualifications needed to thrive as a model predictive control engineer, and why are they important?

To thrive as a Model Predictive Control Engineer, you need strong foundations in control theory, applied mathematics, and process engineering, usually supported by a degree in engineering or a related field. Proficiency with simulation tools such as MATLAB/Simulink, programming languages like Python or C++, and familiarity with industrial automation systems are typically required. Analytical thinking, problem-solving abilities, and effective communication skills help distinguish top performers in this role. These skills are essential for designing, implementing, and optimizing advanced control algorithms that improve system performance and reliability in complex industrial environments.

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

AspectModel Predictive ControlControl Systems Engineer
CredentialsEngineering degree, control theory, process modelingEngineering degree, control systems, automation
Work EnvironmentIndustrial automation, process control, manufacturingDesign, develop, and maintain control systems across industries
Industry UsageProcess industries, chemical, oil & gas, manufacturingAutomation, robotics, embedded systems, industrial sectors

Model Predictive Control (MPC) focuses on advanced control algorithms for optimizing processes, while Control Systems Engineers design and implement various control systems. MPC is a specialized skill within control engineering, often requiring knowledge of process modeling and optimization, whereas Control Systems Engineers have broader responsibilities across multiple control technologies. Both roles are essential in industrial automation but differ in scope and application.

What does a model predictive control do?

A Model Predictive Control (MPC) engineer designs control systems that use a mathematical model to predict future system behavior and optimize control actions accordingly. MPC is commonly used in industries like process control and robotics, requiring skills in control theory, programming, and system modeling. The role involves developing algorithms, tuning controllers, and ensuring system stability and efficiency.

What are popular job titles related to Model Predictive Control jobs in Oregon?

For Model Predictive Control jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Model Predictive Control jobs in Oregon look for?

The top searched job categories for Model Predictive Control jobs in Oregon are:

What cities in Oregon are hiring for Model Predictive Control jobs?

Cities in Oregon with the most Model Predictive Control job openings:

Infographic showing various Model Predictive Control job openings in Oregon as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Assistant/Associate/Full Professor of Bioengineering: Synthetic Biology (2 positions)

Eugene, OR • On-site

University of Oregon
Colleges, Universities, and Professional Schools • 5 - 10K employees

Contractor

Medical, Retirement, PTO

Re-posted 8 days ago


Key responsibilities

  • Design, construct, and engineer biological systems and technologies related to synthetic biology.

  • Employ quantitative, predictive, and design-based approaches to create, modify, or control biological functions.

  • Engage in research activities centered on experimental or computational synthetic biology, including genome engineering and system modeling.


University Of Oregon rating

7.4

Company rating: 7.4 out of 10

Based on 48 frontline employees who took The Breakroom Quiz


Job description

Assistant/Associate/Full Professor of Bioengineering: Synthetic Biology (2 positions)
Job no: 536687
Work type: Faculty - Tenure Track
Location: Eugene, OR
Categories: Biology/Life Sciences, Research/Scientific/Grants, Instruction, Engineering/Biomedical Engineering
Department: Knight Campus Department of Bioengineering
Rank: Assistant/Associate/Full Professor (Open Rank)
Annual Basis: 9 Month
Positions Available: 2
Application Deadline
October 31, 2026; position open until filled
Required Application Materials
To receive full consideration, applicants must submit a complete application including:
• A letter of interest that briefly expresses the candidate's enthusiasm for the role and highlights their track record in growing and strengthening community through collaborative efforts and coalition-building. (including a Google Scholar link)
• CV outlining work history and professional qualifications relevant to this position.
• Statement of current and future research interests and plans.
• Statement describing experience with inclusive teaching and mentoring practices that promote students' success.
• Names and contact information for three professional references.
Position Announcement
1. Experimental & Translational Synthetic Biology:
Examples include, but are not limited to, mammalian synthetic biology; the design and construction of genetic circuits and biosensors; metabolic and pathway engineering for biomanufacturing of chemicals, therapeutics, and sustainable materials; protein and enzyme engineering; genome editing and synthetic genomics tools; engineered cells, consortia, and living biomaterials; host-microbe and microbiome engineering; cell-free and in vitro synthetic biology systems; magnetogenetics; and engineered cell and gene therapies and the platforms that support their manufacture.
**Applicants should demonstrate a research program centered on the engineering of biological systems and technologies and employ quantitative, predictive, and design-based approaches to create, modify, or control biological function.
2. Computational Synthetic Biology:
Examples include, but are not limited to, computer-aided design, lab automation, and autonomous experimentation for the design-build-test-learn cycle; fitness landscape modeling and sequence-function prediction; genome-scale metabolic and dynamical modeling to optimize biomanufacturing and bioprocess design; machine learning, biological foundation models, and generative AI approaches for protein, enzyme, genome, and regulatory sequence design; predictive modeling of engineered cells, microbial communities, biomaterials, and cell and gene therapy products; computational methods for genome engineering and synthetic genome design; design and analysis of engineered regulatory networks; and multi-omics integration and quantitative modeling to guide the design and engineering of biological systems.
Department or Program Summary
The Department of Bioengineering is the largest academic unit within the Knight Campus. The Phil and Penny Knight Campus for Accelerating Scientific Impact is a bold initiative designed to accelerate the translation of scientific discoveries into innovations that improve lives in Oregon, the nation, and beyond. Building on the University of Oregon's tradition of interdisciplinary collaboration, the Knight Campus advances research partnerships, industry engagement, and experiential training for the next generation of scientists, engineers, and entrepreneurs.
Faculty expertise spans regenerative medicine, human performance, biofunctional materials, medical devices and biosensors, neural engineering, and synthetic biology. With the opening of its second research facility, the Knight Campus has doubled its capacity for biomedical research and technology development, expanded space for academic programs and startup incubation, and launched a state-of-the-art BioFoundry. Together, the two facilities provide more than 360,000 square feet dedicated to research, education, innovation, and entrepreneurship.
Additional information about the Knight Campus can be found at knightcampus.uoregon.edu
Minimum Requirements
• Doctorate in Engineering, Biology, Human Physiology, Chemistry, Physics, Computer Science, or related discipline from an accredited institution of higher education.
• Evidence of successful mentoring of trainees at any level (e.g., undergraduate, graduate, postgraduate, postdoctoral, peers).
• Record of research excellence appropriate to career stage in synthetic biology, biological engineering, bioengineering, systems biology, computational biology, or related fields, as evidenced by peer-reviewed publications and extramural funding.
• Demonstrated commitment to fostering an inclusive environment, as evidenced through research, teaching, mentoring, or service.
Preferred Qualifications
• Demonstrated expertise in experimental or computational synthetic biology, including engineered biological systems, genome engineering, synthetic genomics, biomanufacturing, biological design automation, machine learning-enabled biological design, or related areas.
• Demonstrated use of quantitative, predictive, and design-based approaches to engineer, modify, or control biological function and advance synthetic biology through engineering innovation.
• A nationally recognized track record of scientific achievement as evidenced by an outstanding publication record and other appropriate external indicators relevant to the individual's seniority in the field.
• Experience working in complex, multi-stakeholder environments with the ability to build successfully at multiple interfaces (e.g., UO colleges and departments, other Oregon universities, and industry).
• Demonstrated experience with large government agencies, foundations, industry, and philanthropy with a thorough understanding of funding opportunities and pathways, and strategies to successfully attract funding sufficient for the individual's research program and ambitions as relevant to the individual's seniority in the field.
• Demonstrated commitment to translating research discoveries into applications that improve human health.
• Demonstrated commitment to diversifying the pipeline of participants in science training and careers.
• Demonstrated success in a pedagogical environment using evidence-based pedagogical methods.
• Demonstrated service contributions and leadership in academia, research societies, government, and/or industry relevant to the individual's seniority in the field.
About the University
The University of Oregon is building a faculty committed to meeting the needs of our changing student body and creating essential knowledge for society. We encourage applications from individuals who want to join an institution committed to addressing complex problems at all scales, and critical thinking and cross-disciplinary dialogue. We believe the way to create the faculty we need is to develop the most inclusive applicant pool. Goal 03 of our strategic plan, titled Oregon Rising, is to Create a Flourishing Community. As outlined in Oregon Rising, "Flourishing is the holistic development and thriving of every individual in our diverse community achieved through growth, well-being, resilience, trust, belonging, robust connection, and sense of purpose. A flourishing community is built on collective experience and is made stronger by our shared commitment to one another.
All offers of employment are contingent upon successful completion of a background check.
The University of Oregon is proud to offer a robust benefits package to eligible employees, including health insurance, retirement plans, and paid time off. For more information about benefits, visit our website.
The University of Oregon is an equal-opportunity institution committed to cultural diversity and compliance with the Americans with Disabilities Act. The University encourages all qualified individuals to apply and does not discriminate on the basis of any protected status, including veteran and disability status. The University is committed to providing reasonable accommodations to applicants and employees with disabilities. To request an accommodation in connection with the application process, please email us or call 541-346-5112.
UO prohibits discrimination on the basis of race, color, religion, national origin, sex, sexual orientation, gender identity, gender expression, pregnancy (including pregnancy-related conditions), age, physical or mental disability, genetic information (including family medical history), ancestry, familial status, citizenship, service in the uniformed services (as defined in federal and state law), veteran status, expunged juvenile record, and/or the use of leave protected by state or federal law in all programs, activities and employment practices as required by Title IX, other applicable laws, and policies. Retaliation is prohibited by UO policy. Questions may be referred to the Office of Equal Opportunity and Access. Contact information, related policies, and complaint procedures are listed here.
In compliance with federal law, the University of Oregon prepares an annual report on campus security and fire safety programs and services. The Annual Campus Security and Fire Safety Report is available online.
Advertised: August 6, 2026 Pacific Daylight Time
Applications close:

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