[Job-offers-cs] Postdoctoral Appointee - Federated Learning and Distributed Computing

[Pekka Orponen]

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.

Link to apply: Postdoctoral Appointee - Federated Learning and 
Distributed Computing 
<https://argonne.wd1.myworkdayjobs.com/en-US/Argonne_Careers/job/Postdoctoral-Appointee---Federated-Learning-and-Distributed-Computing_418597>


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Kibaek Kim, PhD
Computational Mathematician
Mathematics and Computer Science Division
Argonne National Laboratory, USA
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