Pacific Northwest National Laboratory PhD Intern - Extreme Scale Machine Learning in RICHLAND, Washington

Organization and Job ID

Job ID: 306189

Directorate: Physical & Computational Sciences

Division: Advanced Comput, Math & Data

Group: High Performance Computing


Job Description

The High Performance Computing (HPC) group at Pacific Northwest National Lab seeks a summer intern to conduct research in designing extreme scale Machine

Learning (ML) algorithms on HPC systems. Applicants interested in applying ML

algorithms to HPC problems are also encouraged to apply.

During the summer, student is expected to conduct research on designing ML scalable algorithms under power, reliability constraints; apply ML techniques to solving HPC problems such as reliability modeling, etc.


Minimum Qualifications

Candidates must be currently enrolled/matriculated in a PhD program at an accredited college. Minimum GPA of 3.0 is required.


Preferred Qualifications

Parallel Programming: Basic understanding of MPI, OpenMP, or Spark

Machine Learning Algorithms: Basic understanding of clustering, Support

Vector Machines or Deep Neural Networks (Caffe, TensorFlow, Torch etc)

Architectures/Networks: Basic Understanding of GPUs, Intel KNC/KNL,

InfiniBand, or Intel Omni-Path

Pursuing PhD in Computer Science, Electrical Engineering or related field.


Equal Employment Opportunity

PNNL is an Equal Opportunity/Affirmative Action Employer that is committed to hiring a diverse, talented workforce. EOE Disability/Vet/M/F/Sexual Orientation/Gender Identity. Staff at PNNL must be able to demonstrate the legal right to work in the United States.


Directorate: Physical & Computational Sci's

Job Category: Master's and PhD Level Internships

Group: High Performance Computing

Opening Date: 2017-01-06

Closing Date: 2017-01-27