Postdoctoral Appointee - Federated Learning and Distributed Computing - Argonne National Laboratory
Lemont, IL
About the Job
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites candidates to apply for a postdoctoral position in the areas of federated learning and distributed computing.
This postdoctoral appointee will work on integrating Argonne’s federated learning tool (APPFL) and the Globus suite into the Argonne Leadership Computing Facility (ALCF)’s Nexus workflows, supporting the Department of Energy (DOE) user facilities. This position offers a unique opportunity to collaborate with leading scientists from MCS, DSL, and ALCF, and to develop innovative techniques for federated learning and services across multiple facilities.
Key Responsibilities:
+ Develop and implement techniques for integrating APPFL and the Globus suite into Nexus workflows.
+ Collaborate closely with scientists from MCS, DSL, and ALCF to understand their needs and develop customized solutions.
+ Create new methods and algorithms for federated learning that can be applied across multiple DOE user facilities.
+ Contribute to the expansion of the federated learning and distributed computing capabilities, enhancing its services and usability.
+ Participate in interdisciplinary research projects and contribute to scientific publications.
+ Present research findings at national and international conferences.
Position Requirements
Required skills and qualifications:
+ Recently or soon-to-be completed Ph.D. (within the last 0-5 years) in Computer Science, Applied Mathematics, Electrical Engineering, or a related field
+ Skilled in federated learning, distributed computing, or machine learning.
+ Experience with software development and integration, particularly in high-performance computing environments.
+ Proficiency in Python.
+ Excellent communication and teamwork skills, with the ability to work in a multidisciplinary environment.
Preferred skills and qualifications:
+ Experience with scientific computing workflows and data management.
+ Knowledge of DOE user facilities and their computational needs.
+ Demonstrated ability to conduct independent research and contribute to collaborative projects.
+ High performance computing (HPC) experience.
Job Family
Postdoctoral Family
Job Profile
Postdoctoral Appointee
Worker Type
Long-Term (Fixed Term)
Time Type
Full time
_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._
This postdoctoral appointee will work on integrating Argonne’s federated learning tool (APPFL) and the Globus suite into the Argonne Leadership Computing Facility (ALCF)’s Nexus workflows, supporting the Department of Energy (DOE) user facilities. This position offers a unique opportunity to collaborate with leading scientists from MCS, DSL, and ALCF, and to develop innovative techniques for federated learning and services across multiple facilities.
Key Responsibilities:
+ Develop and implement techniques for integrating APPFL and the Globus suite into Nexus workflows.
+ Collaborate closely with scientists from MCS, DSL, and ALCF to understand their needs and develop customized solutions.
+ Create new methods and algorithms for federated learning that can be applied across multiple DOE user facilities.
+ Contribute to the expansion of the federated learning and distributed computing capabilities, enhancing its services and usability.
+ Participate in interdisciplinary research projects and contribute to scientific publications.
+ Present research findings at national and international conferences.
Position Requirements
Required skills and qualifications:
+ Recently or soon-to-be completed Ph.D. (within the last 0-5 years) in Computer Science, Applied Mathematics, Electrical Engineering, or a related field
+ Skilled in federated learning, distributed computing, or machine learning.
+ Experience with software development and integration, particularly in high-performance computing environments.
+ Proficiency in Python.
+ Excellent communication and teamwork skills, with the ability to work in a multidisciplinary environment.
Preferred skills and qualifications:
+ Experience with scientific computing workflows and data management.
+ Knowledge of DOE user facilities and their computational needs.
+ Demonstrated ability to conduct independent research and contribute to collaborative projects.
+ High performance computing (HPC) experience.
Job Family
Postdoctoral Family
Job Profile
Postdoctoral Appointee
Worker Type
Long-Term (Fixed Term)
Time Type
Full time
_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._
Source : Argonne National Laboratory
