Post-doctoral Research Associate

Scientific Software and Applications Division

The Scientific Software and Applications (SSA) Division at the National Center for Supercomputing Applications (NCSA) in collaboration with the Physics Department at the University of Illinois at Urbana-Champaign invite applications for a post-doctoral research associate to perform research at the intersection of machine learning, scientific cyberinfrastructure and high-energy particle physics. Dr. Mark Neubauer and Dr. Daniel S. Katz are looking for a highly motivated postdoc to work on a project funded by the National Science Foundation aimed at developing scalable cyberinfrastructure for artificial intelligence and likelihood-free inference applied to data from the Large Hadron Collider (LHC) at CERN in Geneva, Switzerland.

The project postdoc will work closely with faculty and staff at NCSA as well as Dr. Neubauer's team in the Physics Department and collaborators at NYU (Dr. Kyle Cranmer, Dr. Heiko Mueller) and Notre Dame (Dr. Michael Hildreth). Furthermore, the position will involve interaction with collaborators and students in a range of educational, scientific, and engineering disciplines towards the development of scalable cyberinfrastructure.

The Scalable Cyberinfrastructure for Artificial Intelligence and Likelihood-Free Inference (SCAILFIN) project aims to maximize the potential of artificial intelligence and machine learning to improve new physics searches at the LHC, while addressing current issues in software and data sustainability by making data analyses more reusable and reproducible.

The successful candidate is expected to lead the development of scalable cyberinfrastructure for the SCAILFIN project along one or more of the following research threads:

  • Machine learning methods for approximate likelihood and likelihood-free inference in the context of LHC data.
  • Parsl-based workflows in the context of a Reusable Research Data Analysis Platform (REANA).
  • Containerization of data analysis workflows and execution on distributed computing resources and HPCs such as Blue Waters.

Required education and experience

  • A Ph.D., or equivalent, in particle physics, computer science, data science or related fields is required at the time of application.
  • Experience in software development in a scientific context.
  • Ability to clearly communicate results and their importance (verbally and in writing).

Preferred experience

  • Proficient at programming in Python
  • Familiarity with C++
  • Familiarity with workflow systems used for data analysis
  • Familiarity with container technologies such as Docker, Shifter/Singularity, Kubernetes
  • Contributions towards research publications
  • Experience in one or more of the following:
    • Applying Machine Learning to challenges within a scientific domain
    • Processing of high-volume data
    • Exploring the preservation and reuse of data, software, and analysis products
    • HPC/HTC environments, cloud computing, and/or systems administration

Key skills/knowledge

Strong candidates will also possess the following attributes:

  • A strong publication record from their PhD (papers published, in press, or submitted).
  • Creativity, independence, and the desire to learn new things.
  • Ability to work within and excel in large research collaborations.
  • Excellent communication skills, both written and oral.
  • Skilled in scientific software development, including open source development best practices and tools.
  • Contributions to publications, technical reports, and documentation.
  • Ability to provide input for reports, presentations, and grant proposals.

For full consideration, all application materials should be submitted to Dr. Daniel S. Katz and Dr. Mark Neubauer by December 16, 2018. Applications should include a brief cover letter, curriculum vitae, and the names and contact information for three references. Please put "postdoc application" in the subject line of your email.

Any offer for this position is contingent upon your successful completion of a criminal background check process in accordance with the University of Illinois Background Check Policy. Once an offer has been made and accepted, as part of the hiring process, you will receive an email from The background check process will not begin until you provide authorization by responding to the email from Please respond promptly to this request.

Dr. Daniel S. Katz
National Center for Supercomputing Applications
University of Illinois

Dr. Mark Neubauer
Physics, College of Engineering
University of Illinois

Illinois is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, age, status as a protected veteran, or status as a qualified individual with a disability. Illinois welcomes individuals with diverse backgrounds, experiences, and ideas who embrace and value diversity and inclusivity. Visit

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