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Pittsburgh Supercomputing Center is a joint computational research center with Carnegie Mellon University and the University of Pittsburgh. Established in 1986, PSC is supported by several federal agencies, the Commonwealth of Pennsylvania and private industry.

PSC provides university, government and industrial researchers with access to several of the most powerful systems for high-performance computing, communications and data storage available to scientists and engineers nationwide for unclassified research. PSC advances the state of the art in high-performance computing, communications and data analytics and offers a flexible environment for solving the largest and most challenging problems in computational science.

This position will involve working closely with the Neocortex computing platform as well as members of the AI and Big Data group that support this machine. Neocortex is a highly innovative resource that enables fast training of deep learning transformer and vision models. Neocortex is equipped with CS-2 (Cerebras wafer scale engine) chips, the largest ever built. The Cerebras chip are accompanied by the Cerebras modelzoo, which has implementations of “popular” transformer architectures for use on Neocortex. For this position, you will be developing and using different transformers in the Cerebras modelzoo for a variety of chemistry related tasks, such as text summarization of papers from arXiV, predictions of organic synthesis reactions, and molecule generation. The goal of this project is to showcase the ability of Neocortex to be used in different chemistry contexts. The results of this project will be disseminated at conferences and publications. You will be responsible for writing and running compatible code on Neocortex as well as running and analyzing these experiments.

Responsibilities may include:

  • Code development for the Neocortex machine
  • Conducting and analyzing experiments

Our internships offer the opportunity to:

  • Gain valuable experience and knowledge in research computing.
  • Network with leaders in academia and industry to form valuable relationships.
  • Publish in peer-reviewed journals and at prominent conferences.
  • Gain experience with an innovative computing architecture.
  • Develop skills relevant to the field of machine learning, including data curation, model porting, and evaluating model performance.      

Job Requirements      
Successful candidates will have the following:

  • Candidates must be pursuing an undergraduate (bachelor’s) degree. Examples of relevant majors are computer science, and natural sciences that are also focusing on computational work (i.e. chemistry, physics)
  • Excellent communication skills and ability to work in a team environment.
  • Excellent problem-solving skills and creativity.