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Postdoctoral Appointee – Virtual Drug Response Prediction
Requisition Number: 408102 Location: Lemont, IL
Functional Area: Research and Development Division: LCF-Leadership Computing Facility
Employment Category: Temporary 6 Months or Greater Education Required: Not Indicated
Level (Grade): 700 Shift: 8:30 - 5:00
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The Argonne Leadership Computing Facility (ALCF) has an immediate opening for a postdoctoral researcher to work on novel data-driven scientific discoveries for cancer research targeting our forthcoming exascale supercomputer, Aurora. The ALCF enables breakthroughs in science and engineering by providing supercomputing resources and expertise to the research community.

You will collaborate with scientists in the Early Science Program (ESP) to solve some of the most challenging scientific problems on America’s first Exascale supercomputer, Aurora, to be deployed in 2021. The successful candidate will work with an inter-disciplinary team of scientists to develop data-driven techniques using machine learning and deep learning for drug design and predictive models for drug response to help in the treatments of cancer patients. You will work in a multi-disciplinary and collaborative environment consisting of computational scientists, experimental and computational biologists, computer scientists, applied mathematicians, and ML/DL experts.

In this role you will:

  • Research and develop data-driven models for drug design and predictive models for drug response that can be used to optimize pre-clinical drug screening and drive precision medicine-based treatments for cancer patients.
  • Research and develop novel high-throughput workflows to effectively scale the drug-design model on supercomputers.



 We expect you to have:  

  • A PhD + 0-3 years in computational sciences including chemistry, computer science, physics, iology, or in a related field.
  • Comprehensive experience programming in one or more programming languages such as C, C++, and Python.
  • Experience with data-driven modeling.
  • Knowledge of numerical methods, parallel programming, machine learning/deep learning methods and frameworks.
  • Knowledge of parallel algorithms, distributed memory architectures, and parallel performance evaluation of domain specific implementations.
  • Ability to create, maintain, and support high-quality software.
  • An ideal candidate would have published their scientific software in a public repository (e.g. GitHub)]
  • Interpersonal and communication skills required to interact effectively, tactfully and discreetly with all nternal/external contacts and to develop effective working relationships.
  • Must have considerable ability to proactively identify issues, investigate, and recommend solutions.
  • Ability to think quickly and problem-solve when managing difficult situations.
  • Ability to  model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork. 

As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.

All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

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