Postdoctoral Appointee - Fault Tolerant Distributed Systems
- Argonne National Laboratory
- Location: Lemont, USA
- Job Number: 7202617 (Ref #: 416991)
- Posting Date: Dec 21, 2023
Job Description
The Data Science and Learning Division at Argonne National Laboratory invites applications for several Postdoctoral Appointee positions beginning as soon as possible. This is a fixed-term, fiscal year (twelve month) appointment with the possibility of extension annually based on satisfactory performance and funding availability.
The Diaspora project, led by Professor Ian Foster, aims to develop new methods for building next-generation resilient scientific applications capable of executing in an increasingly integrated research infrastructure. These applications will provide novel capabilities to run large-scale distributed computations, connect large scale scientific instruments with modern computing environments, and integrate distributed data sources, all with the goal of greatly increasing the speed and reliability of scientific discovery.
In this role you will be a part of a multi-institutional and interdisciplinary team composed of Argonne National Laboratory, Texas Tech, Oak Ridge National Laboratory, and SLAC National Accelerator Laboratory, funded by the Department of Energy, Department of Energy’s Office of Advanced Scientific Computing Research.
The Postdoctoral Appointees will be expected to conduct research in one or more of the following themes:
- Scalable event propagation services for high performance computing systems with features required by scientific applications.
- Resilience-enabling services on top of events, such as resilient data pipelines for streaming analysis and resilient data views.
- Resilient communication and data streaming among computing platforms and instruments that exploit redundant computations and network paths.
- Connecting streaming data sources (e.g., Argonne’s Advanced Photon Source, gravitational wave observatories, supercomputers) to modern computing environments, and demonstrating the resilient building blocks with production scale scientific applications.
Position Requirements
Required skills and qualifications:
- A recent or soon-to-completed PhD (typically within 0-3 years) in computer science, physics, or a related discipline.
- Evidence of effectively communicating research through conference presentations and/or journal papers.
- Effective written and verbal communication skills and the ability to work independently and as a part of a team.
- Commitment to working with diverse faculty, staff, students, and communities.
- Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork.
Desired skills and qualifications:
- Expertise in computer science, supercomputing, machine learning, AI.
Application materials required:
Upon submitting your application, please include the following items:
- Cover letter
- Current curriculum vitae with publication list
- 2 page summary of research experience and interests
Later in the process, you may be asked to provide three letters of recommendation from three professional contacts.
The initial deadline to apply is January 31, 2024. If all positions are not filled by that time, applications will be evaluated until all positions are filled.
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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