- Princeton - New Jersey - États-Unis d'Amérique
Reasoning on Graph Representations in Engineering Design - Internship
Reasoning on Graph Representations in Engineering Design - Internship
We are looking for a talented intern who would like to join our Design and Representation Systems Research Group of the “Simulation and Digital Twin” Technology field for a fixed-term internship.
We need your help to conduct fundamental and applied research in the field of understanding engineering decisions for complex systems. You will be collaborating with leading academic institutions and government agencies as part of this role. Our goal is to model how engineers understand and solve the most complex design challenges by leveraging AI techniques and mimic human reasoning capabilities!
Transform the Everyday with us!
In this role you will work on-site in Princeton, NJ.
Responsibilities:
During this internship, the candidate will experience the excitement and challenges of industrial research and be part of a world class team. This person will:
- Contribute to the task of exploring reasoning over graph representations using graph neural networks.
- Work on the task of exploring application of graph neural networks to engineering design.
- Work on fast-paced co-creation projects with quickly changing requirements in the field at the intersection of machine learning and engineering design.
- Work on low-TRL research projects.
- Work with Siemens software products (e.g., Capital) to develop demonstrators and participate in technology transition to Siemens’ businesses.
- Develop demonstrators and participate in technology transition to business.
- Create technical reports.
- Create academic publications.
Required Qualifications:
- PhD students in Mechanical Engineering, Aerospace Engineering, Electrical Engineering, Computer Science, or related discipline.
- Research specialization in the application of AI/ML for engineering design.
- Research specialization in graph neural networks and generative models.
- Familiarity with techniques involving handling large scale graphs.
- Familiar with integration of graph neural networks with knowledge graphs.
- Proficiency in python, PyTorch and PyG.
- English language skill both written and verbal
- Legal authorization to work in the United States without company sponsorship now or in the future.
About Us
We want to provide our customers with Innovative Design solutions and propose intelligent representations for faster and smarter design, engineering, and manufacturing systems. Our team is to become the perfect companions for engineers in need to accelerate by 1000x their workflows. Our mission is to free engineers from the burden of repetitive and non-creative tasks and allow them to truly explore the immensity of their design spaces, efficiently and with confidence in the results. We want to be “Your cognitive twin”, enabling machines to reason and make decisions autonomously.
Our research team is located in beautiful Princeton, NJ, a university town packed with exceptional international talent that provides a unique feel of this true cultural gem in the state. The town has plenty of activities to offer, but for those looking for more, at just about 1h drive we have NYC or Philadelphia. We have the best public schools in the country and all of the above glued together by a very active and welcoming community.
As Siemens’ central Research & Development department, we embrace this community. Our core mission is to support our Siemens business units as a central knowledge hub for all cybersecurity capabilities globally. We research and develop new and innovative solutions, based on much needed deep technical expertise, and our network with internal and external experts and academia. This allows us to invent new solutions and approaches and verify their feasibility in the “real world” together with the product development teams of our business units – creating a stimulating setup for quick innovation cycles and rapid prototyping.
About Siemens:
We are a global technology company focused on industry, infrastructure, transport, and healthcare. From more resourceefficient factories, resilient supply chains, and smarter buildings and grids, to sustainable transportation as well as advanced healthcare, we create technology with purpose adding real value for customers. Learn more about Siemens here.
Our Commitment to Equity and Inclusion in our Diverse Global Workforce:
We value your unique identity and perspective. We are fully committed to providing equitable opportunities and building a workplace that reflects the diversity of society, while ensuring that we attract the best talent based on qualifications, skills, and experiences. We welcome you to bring your authentic self and transform the everyday with us.
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Siemens offers a variety of health and wellness benefits to our employees. Details regarding our benefits can be found here: https://www.benefitsquickstart.com/siemens/index.html
The pay range for this position is $32-$45 per hour. The actual wage offered may be lower or higher depending on budget and candidate experience, knowledge, skills, qualifications and premium geographic location.
Déclaration d’égalité des chances en matière d’emploi
Siemens est un employeur garantissant l’égalité des chances, qui promeut l’inclusion sur le lieu de travail. Tous les candidats qualifiés seront examinés pour un emploi sans distinction de race, couleur, croyance, religion, origine nationale, statut de citoyenneté, ascendance, sexe, âge, handicap physique ou mental sans lien avec les capacités, statut marital, responsabilités familiales, grossesse, informations génétiques, orientation sexuelle, expression ou identité de genre, transidentité, stéréotypes liés au sexe, statut de protection, statut d’ancien combattant ou militaire protégé, ou encore en cas de libération défavorable du service militaire, ainsi que toute autre catégorie protégée par la législation fédérale, étatique ou locale.
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Les candidats et employés sont protégés contre toute discrimination fondée sur la race, la couleur, la religion, le sexe, l’origine nationale ou toute autre caractéristique protégée par la loi fédérale ou toute autre législation applicable.
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Transparence des rémunérations
Siemens respecte les lois sur la transparence salariale.
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