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UID:submissions.supercomputing.org_SC23_sess503_job126@linklings.com
SUMMARY:Research Scientist, High Performance Computing and Artificial Inte
 lligence (Hybrid Eligible)
DESCRIPTION:Overview:\nReady to apply your HPC and AI skills in a premier 
 research institution? The Analytics and AI methods at Scale (AAIMS) group 
 in the National Center for Computational Science (NCCS) is seeking hardwor
 king research scientists in the very broad areas of intersection of High-P
 erformance Computing (HPC) and AI. Examples on areas of research interest 
 include: \n\nNLP and Foundational model pre-training, human-in-loop reinfo
 rcement learning and fine-tuning. \n\nPerformance analysis and optimizatio
 n of large-scale AI/ML stack and applications including computational opti
 mization of mixed-precision kernels, data parallelism, model-parallelism, 
 collective communication patterns and strategies for large-scale, distribu
 ted machine learning using frameworks such as PyTorch and TensorFlow. \n\n
 Operational data (Power, energy, CPU/GPU utilization, job scheduling, larg
 e scale storage and I/O traces, system logs) analytics to enable data-driv
 en intelligence and facility innovation via novel applications of ML/AI te
 chniques such as large-scale language model and causality analysis. \n\nAI
  algorithms for handling sensitive data using methods such as Federated Le
 arning, Differential Privacy, and Secure Multiparty Computing, among other
 s. \n\nData analytics pipelines from the Edge to Exascale. \n\nVisualizati
 on of large-scale HPC/AI discovery campaigns. \n\nAt the NCCS and its Lead
 ership Computing Program (OLCF,) we provide world class computing faciliti
 es to applications across all computational domains and subject areas. Thr
 ough this position you are able to impact and further the mission of NCCS 
 and Oak Ridge National Laboratory. We are a diverse, dynamic environment t
 hat welcomes those with initiative and creativity. \n\nMajor Duties and Re
 sponsibilities:\nResearch, develop and deploy new groundbreaking tools and
  frameworks of scalable ML/DL on leadership computing platforms. \nIn coll
 aboration with domain scientists, identify and extract ML/DL workflow, and
  patterns, and drive the design, development, and deployment of new scalab
 le ML-as-service solutions. \nEngage with ML academic communities to stay 
 on top of the latest advancements in ML/DL. Author peer reviewed papers, t
 echnical papers, reports, and proposals. \n\nBasic Qualifications:\nPh.D. 
 in Computer Science, Computer Engineering, or a field closely related to t
 he job duties of this position.  \n \nPreferred Requirements:\n3+ years of
  relevant research experience outside of Ph.D. \nExperience leading major 
 projects in laboratory or academic settings. \nStrong publication record a
 nd record of developing high-impact capabilities and tools. \n\nORNL Ethic
 s and Conduct:\nAs a member of the ORNL scientific community, you will be 
 expected to commit to ORNL's Research Code of Conduct. A description and a
  statement by the Lab Director's office can be found here: https://www.orn
 l.gov/content/research-integrity \n\nBenefits at ORNL:\nORNL offers compet
 itive pay and benefits programs to attract and retain hardworking people. 
 The laboratory offers many employee benefits, including medical and retire
 ment plans and flexible work hours, to help you and your family live happy
  and healthy. Employee amenities such as on-site fitness, banking, and caf
 eteria facilities are also provided for convenience.  \n\nOther benefits i
 nclude the following: Prescription Drug Plan, Dental Plan, Vision Plan, 40
 1(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disabilit
 y Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insuranc
 e with Identity Theft Protection, Employee Assistance Plan, Flexible Spend
 ing Accounts, Health Savings Accounts, Wellness Programs, Educational Assi
 stance, Relocation Assistance, and Employee Discounts.  \n\nIn addition, w
 e offer a flexible work environment that supports both the organization an
 d the employee. A hybrid/onsite working arrangement may be available with 
 this position. \n\nIf you have difficulty using the online application sys
 tem or need an accommodation to apply due to a disability, please email: O
 RNLRecruiting@ornl.gov or call 1.866.963.9545.\n\n
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