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Model Predictive Control Jobs in Indiana (NOW HIRING)

... control, and lifecycle management of our clinical diagnostics portfolio and associated laboratory ... Collaborate with Data Analytics to architect predictive inventory modeling systems, monitoring ...

The Fleet Manager will lead a multi-year transformation focused on reliability, cost control, and ... Oversee maintenance strategies, including preventive and predictive maintenance programs. * Drive ...

The Fleet Manager will lead a multi-year transformation focused on reliability, cost control, and ... Oversee maintenance strategies, including preventive and predictive maintenance programs. * Drive ...

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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 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 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 are popular job titles related to Model Predictive Control jobs in Indiana? For Model Predictive Control jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Model Predictive Control jobs in Indiana look for? The top searched job categories for Model Predictive Control jobs in Indiana are:
What cities in Indiana are hiring for Model Predictive Control jobs? Cities in Indiana with the most Model Predictive Control job openings:
Infographic showing various Model Predictive Control job openings in Indiana as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 20% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Postdoctoral Fellow - AI/ML Upstream Cell Culture Modeling & Process Development

Eli Lilly and Company

Indianapolis, IN • On-site

$46K - $63K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago


Eli Lilly and Company rating

8.8

Company rating: 8.8 out of 10

Based on 63 frontline employees who took The Breakroom Quiz

11th of 86 rated pharmaceutical


Job description

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work-but it's work worth doing. If you're driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.
Overview:
At Lilly, we serve an extraordinary purpose. We make a difference for people around the globe by discovering, developing and delivering medicines that help them live longer, healthier, more active lives. Not only do we deliver breakthrough medications, but you also can count on us to develop creative solutions to support communities through philanthropy and volunteerism.
Position Summary:
The Upstream Process Development group within our BR&D organization is seeking a Postdoctoral Fellow to join a team of scientists and engineers focused on developing and optimizing mammalian cell culture processes for recombinant proteins and other modalities for early- and late-phase clinical trials.
This role will focus on developing and applying innovative mathematical and computational modeling approaches to characterize, understand, and predict the complex biological systems used in mammalian cell culture. The fellow will build mechanistic and data-driven models, including genome-scale and hybrid metabolic models, to predict cellular behavior, diagnose process bottlenecks, and rationally guide the design of feeding strategies and medium compositions. Where current development often relies on iterative empirical screening, this position aims to establish a model-guided approach that narrows the experimental search space before committing significant laboratory effort.
The fellow will also explore the use of these models within real-time monitoring and control frameworks, and will leverage machine learning to enable earlier, model-informed decisions such as clone selection based on predicted process performance. The work establishes a closed-loop cycle in which model predictions are validated experimentally and the resulting data continuously improves model accuracy. This position is well suited to a highly motivated scientist who wants to bridge computational modeling and hands-on bioprocess experimentation.
Responsibilities:
  • Develop and calibrate mechanistic and hybrid metabolic models of mammalian cell culture processes, integrating process data to predict cellular behavior and identify performance-limiting factors.
  • Build computational pipelines that turn routine bioprocess data into model inputs and generate predicted metabolic flux distributions across the culture cycle.
  • Apply machine learning and data-driven methods for performance prediction and to integrate model-derived features with experimental data.
  • Use calibrated models to evaluate feeding strategies and medium compositions to enhance productivity.
  • Design and execute cell culture experiments-from shake flask to bench-scale bioreactors-to generate datasets for model development, training, and validation.
  • Collaborate with the Analytical team to develop multi-omics methods for metabolic model calibration.
  • Integrate model-derived features into machine learning workflows to support earlier decisions, including predictive clone selection from earlier-stage process data.
  • Investigate AI-assisted approaches to accelerate model building, validation, and reuse across projects, with human-in-the-loop decision support.
  • Maintain rigorous documentation, communicate results through technical reports, presentations, and peer-reviewed publications, and collaborate across cross-functional teams.

Basic Requirements:
  • PhD in Chemical/Biochemical Engineering, Bioengineering, Systems Biology, Computational Biology, Metabolic Engineering, or a related field.
  • Experience with constraint-based or genome-scale metabolic modeling.
  • Hands-on experience designing and executing cell culture experiments with a working understanding of Batch, Fed-batch, and Intensified Processes.
  • Qualified applicants must be authorized to work in the United States on a full-time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F-1 CPT, F-1 OPT, F-1 STEM OPT, J-1, H-1B, TN, O-1, E-3, H-1B1, or L-1.

Additional Preferences:
  • Strong foundation in mathematical modeling, reaction kinetics, and mammalian cell culture.
  • Proficiency in Python, MATLAB, or similar scientific programming languages.
  • Familiarity with process control concepts, including model predictive control or dynamic optimization.
  • Understanding of mammalian (e.g., CHO) cell physiology and metabolism relevant to bioprocessing.
  • Experience with analytical methods such as HPLC, UPLC, and mass spectrometry is a plus.
  • Experience integrating omics data with mechanistic or hybrid models.
  • Demonstrated expertise in machine learning and data-driven modeling is a plus.

Additional Information:
  • This position is part of Lilly's postdoctoral training program, which provides an exceptional environment and the opportunity for professional growth through learning, collaboration, networking, and mentorship from Lilly's leading scientists, aimed at facilitating groundbreaking discoveries.
  • This position is not permanent. It is for a fixed duration of two years with the potential to extend to a maximum of 4 years. You will have opportunities to apply for full-time positions after your duration is complete.

About Eli Lilly's Postdoctoral Scientist Program:
When it comes to research and development, our goal is to discover and deliver innovative medicines that make life better for people around the world. It's challenging, expensive, and often filled with failure. But even when we fail, we advance medical science and understanding by learning more about diseases, biology, and chemistry-ultimately bringing new solutions one step closer to reality. Over the course of our history, we have shed light on some of the toughest health care problems known to humankind-diabetes, heart disease, infectious diseases, neuroscience disorders, cancer, and more. We could not pursue this without our research and development team.
Postdoctoral scientists help us continue this pursuit. During your experience you will get:
  • Top industry research experience
  • Mentoring by some of Lilly's top scientists
  • Laboratory and classroom training and education to further your development
  • Collaboration and networking across dozens of postdoctoral scientists and other researchers

Physical Demands:
  • The physical demands of this job are consistent with a lab environment.
  • The physical demands here are representative of those that must be met by an employee to successfully perform the essential functions of this job.

Work Environment:
  • This position's work environment is in a laboratory.
  • The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job.
  • *To perform this job successfully, an individual must be able to perform the role and responsibilities satisfactorily. The requirements listed above are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women's Initiative for Leading at Lilly (WILL).
Actual compensation will depend on a candidate's education, experience, skills, and geographic location. The anticipated wage for this position is
$58,000 - $123,200
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly's compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
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About Eli Lilly

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Eli Lilly, based in Indianapolis, IN, US, is one of the pioneers in the pharmaceutical industry with a rich history dating back to 1876. This global pharmaceutical company focuses on discovering, developing, manufacturing and selling pharmaceutical products in approximately 120 countries. The company's product categories include endocrinology, oncology, cardiovascular, neuroscience, and immunology. Having invested over $9 billion in research and development in the past decade, Eli Lilly is also committed to creating high-quality medicines that meet real needs. As a recipient of several awards and recognitions, Eli Lilly is known for its focus on life-saving research and drug development. Their mission is to make medicines that help people live longer, healthier, and more active lives.

Industry

Pharmaceutical product wholesalers

Company size

10,000+ Employees

Headquarters location

Indianapolis, IN, US

Year founded

1876