Postdoctoral Appointee – Machine Learning for X-ray Science
- Argonne National Laboratory
- Location: Lemont, USA
- Job Number: 7245248 (Ref #: 418219)
- Posting Date: May 17, 2024
Job Description
The Scientific Software Engineering & Data Management Group in the X-Ray Science Division (XSD) at the Advanced Photon Source (APS) (https://www.aps.anl.gov/) invites applicants for a postdoctoral position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate the scientific discovery process by quickly extracting useful information from vast quantiles of data, and by providing feedback to the experiment system enabling autonomous control and steering. New fast data reduction approaches and systems will be developed and implemented that operate close to instruments at the edge, and that leverage high-performance computing environments when needed. This position will be funded under a Department of Energy award, “Intelligent Learning for Light Source and Neutron Source User Measurements Including Navigation and Experiment Steering (ILLUMINE).” The selected candidate will work as a part of a multidisciplinary research team comprised of scientists from Scientific User Facilities at several National Laboratories.
The X-ray Science Division (XSD) of Argonne National Laboratory enables world-class research using x-rays by developing cutting edge X-ray instrumentation and techniques, and pursuing research in the physical, chemical, environmental, and materials sciences. To accomplish this mission, XSD fully operates 43 beamlines and is a partner in the operation of three more beamlines at the Advanced Photon Source (APS).
Today, the APS collects approximately 10 PB of raw experimental data per year from approximately 100 sophisticated instruments performing work in a variety of scientific domains. Over the coming decade, the APS anticipates this annual data volume will increase by multiple orders-of-magnitude. This is an exciting opportunity to be at the forefront of using advanced computational methods and systems, including machine learning, to develop data and computing solutions needed to answer pressing scientific questions that face the nation today.
The successful candidate will perform R&D and other activities to collaboratively develop and apply new approaches for intelligent learning and autonomous control for light source data and experiments. The successful candidate will implement and deploy these approaches for use on facility beamlines, evaluate the results, and disseminate findings through scholarly journals and conferences.
Questions about this position should be directed to nschwarz@anl.gov.
Position Requirements
Position Requirements:
To qualify for this position, you must have obtained your PhD in computer science or engineering, the physical sciences, or a related field within the last three years.
Comprehensive programming proficiency, preferably in Python.
Experience with machine learning methods and frameworks especially applied to physical science problems.
Experience with x-ray data analysis and/or modeling, such as crystallography, diffraction, or spectroscopy data analysis and/or modeling.
Skill in written and oral communications.
Working knowledge of UNIX or Linux.
Ability to work as part of a team to solve problems of scientific and technological interest to the APS.
Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
Understand, value, and promote diversity.
Preferred Experience:
Experience with synchrotron light source / x-ray free electron laser experiments.
Experience using high-performance computing systems and facilities.
Experience using and deploying applications on edge devices.
Job Family
Postdoctoral FamilyJob Profile
Postdoctoral AppointeeWorker Type
Long-Term (Fixed Term)Time Type
Full timeAs 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.
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