Deep Learning-Driven Modeling Internship

Job Description

Deep Learning-Driven Modeling Internship


Description:

Are you interested in driving the next generation of design and modeling tools using deep learning in real industrial applications?

Here’s the right internship opportunity for You!

Join our Product Modeling and Simulation Research Group (PSM RG) to develop solutions to real-world problems. The CT Simulation and Digital Twin Technology Field (SDT TF) is seeking a highly motivated Master/PhD student available for an internship in the area of deep learning-driven modeling.

The Product Design, Modeling and Simulation Research Group is the lead organization of a project funded through Defense Advanced Research Projects Agency (DARPA) Transformative Design (TRADES) program where the goal is to design and implement a comprehensive suite of technologies, including technologies that can combine the strengths of machine learning and advanced optimization strategies for steering the optimization process for rapid and intuitive realization of multi-functional, multi-scale, and multi-material products. It also partners with top US universities in projects funded by agencies like Digital Manufacturing and Design Innovation Institute and America Makes to advance the tools and technologies for new generation digital design and manufacturing tools.

Our Princeton facility is recognized for providing a stimulating environment for highly talented and self-motivated students. You will have the opportunity to test your knowledge in a challenging problem-solving environment. You will be encouraged to think out-of-the-box, innovate and find solutions to real-life problems. Our team has a strong publication record in leading journals and conferences. Our close contact to different business units in Siemens provide the opportunity for you to contribute and gain experience in real industrial applications. During this internship, you will experience the excitement and challenges of industrial research. An internship with Siemens Corporate Technology is a great opportunity for students to gain real world experience in a diverse work environment.


What are my responsibilities?

What skills are needed to qualify for this internship?

  • A Master or PhD student in Computer Science, Mechanical Engineering, electrical engineering or related discipline for research 
  • At least 1 year of experience in advanced algorithm prototyping
  • At least 2 years hands-on programming experience in Python, MATLAB and C++, C# and Web APIs and other mainstream programming languages to quickly prototype
  • Prior experience in deep learning and other machine learning methods (e.g. reinforcement learning, Bayesian models, convolutional neural network, recurrent neural network)
  • Experience with one machine learning tool, such as Pytorch, Tensorflow, Keras, Scikit, Theano, etc.
  • Familiarity with different machine learning architectures
  • Excellent team working and communication (verbal & written) skills
  • Flexibility and adaptability to work in a growing, dynamic, interdisciplinary team of experts.
  • Successful candidate must be able to work with controlled technology in accordance with US Export Control Law. US Export Control laws and applicable regulations govern the distribution of strategically important technology, services and information to foreign nationals and foreign countries. Siemens may require candidates under consideration for employment opportunities to submit information regarding citizenship status to allow the organization to comply with specific US Export Control laws and regulations. Additional information on the US Export Control laws & regulations can be found on https://www.bis.doc.gov/index.php/policy-guidance/deemed-exports/deemed-exports-faqs 

URCT




Job ID: 180001

Organization: Corporate Technology

Company: Siemens Corporation

Experience Level: Student (Not Yet Graduated)

Job Type: Full-Time temporary



Equal Employment Opportunity Statement
Siemens is an Equal Opportunity and Affirmative Action Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, protected veteran or military status, and other categories protected by federal, state or local law.

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