AspenTech is the world’s leading supplier of asset optimization software solutions. From our roots at MIT over 35 years ago to technology breakthroughs today that extend the reach of optimization, AspenTech has always been at the forefront of innovation. AspenTech’s Research & Development team consists of industry-leading experts in the field of process modeling, control, planning and optimization. On this team you will have the opportunity to turn creative ideas into reality, affecting products that are utilized by hundreds of thousands of users worldwide.
We are looking for talented interns to join our industrial artificial intelligence and modeling team in or Houston TX for a for a three to four-month internship. During this time, you will help conduct applied research towards our vision of a self-optimizing plant. You will utilize state of the art algorithms and results from academia to help refine digital twin representations or model plant interactions.
- Create innovative technology at the intersection of domain expertise and industrial AI
- Contribute on applied research towards a self-optimizing plant
- Develop prototypes and proof of concepts
- Develop demonstrators and participate in technology transition to business
- Create technical reports
What You’ll Need
- Graduate student in Science, Engineering or related discipline
- Research specialization in machine learning/artificial intelligence, mathematical modeling and optimization
- Experienced Python programmer
- Knowledge in C++ or C# is a plus
- Familiarity with big data and cloud technologies is a plus
- Familiarity with chemical engineering or related fields is a plus
- Problem-solving ability and attention to details
- Excellent interpersonal, communication, writing, and presentation skills
AspenTech is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, creed, sex, sexual orientation, gender identity, national origin, disability, or protected Veteran Status or any other basis protected by federal, state, or local law.