Website Oak Ridge National Laboratory

Overview:

We are seeking a Research Scientist/R&D Staff Member to work on Natural Language Processing (NLP) projects that leverage state-of-the-art deep learning models, high performance computing, and large datasets of unstructured clinical text. Example problems include extracting topography and morphology information from cancer pathology reports, using the Summit supercomputer to pretrain state-of-the-art Transformer language models for clinical and biomedical text, and developing privacy-preserving deep learning models that generalize well to clinical organizations across the US. There is flexibility in defining new research directions relevant to the problems and projects being tackled. The position will be in the Biostatistics and Multiscale Systems (BMS) group in the Advanced Computing in Health Science (ACHS) Section of the Computational Science and Engineering Division (CSED).

As a research scientist, you will have the opportunity to help solve some of the most challenging problems this world faces. You will perform ground breaking research on a wide range of significant problems with the fastest computing platforms in the world. This position requires novel thinking, teamwork, and discovery in finding new approaches for analyzing massive and complex data, collaborating with worldwide experts, and publishing groundbreaking results.

Major Duties/Responsibilities:

  • Research, design, and implement scalable deep learning NLP solutions for clinical text classification, information extraction, and other related tasks on a dataset composed of several million cancer pathology reports
  • Perform research with scalable Transformer-based models such as BERT using clinical and biomedical text data
  • Author peer reviewed papers, technical papers, reports and proposals for internal and external release and represent the organization by giving technical presentations in large public forums
  • Research and evaluate emerging technologies and approaches in the broader ML community.
  • Quickly and clearly summarize analyses, following best practices in documentation, data visualization, and provenance tracking for reproducibility.
  • Lead and manage technical projects in the expansion of R&D machine learning and imaging while striving to work with and involve other areas of expertise within the laboratory.
  • Present research results to sponsors, peer reviewers, and others and at national and international technical society meetings.
  • Interact with industry and government sponsors in pursuit of new and additional research funding.
  • Network and develop collaborative R&D with other groups and divisions internally and with DOE, the industry, and the utilities.
  • Prepare new proposals to the internal and external funding agencies.
  • Develop research proposals that solicit new and ongoing work in the machine learning and research program.
  • Be a part of a vibrant collaborative research environment which will provide the opportunity to perform cutting-edge research in deep learning and high-performance computing using ORNL’s Leadership Class Supercomputer

Basic Qualifications:

  • PhD in Computational Linguistics, Biomedical/Health Informatics, Data Science, Computer Science, Artificial Intelligence, or other discipline related to the job duties of this position.
  • 2+ years of relevant research experience outside of Ph.D.
  • Experience identifying relevant and novel research directions and generating meaningful research outputs including papers and software
  • Significant experience working with text data and natural language processing techniques
  • Significant experience working with deep learning frameworks like Tensorflow or PyTorch
  • Clear understanding of common data science methodologies and techniques, e.g. supervised and unsupervised learning, feature selection/engineering, hyperparameter optimization, dimensionality reduction, word embeddings, etc.
  • Strong track record of publications in relevant conferences, workshops and journals.

Preferred Qualifications:

  • 5+ years experience working in NLP, ML, DL and/or biomedical/health informatics research outside of Ph.D.
  • Previous publications in high impact deep learning or biomedical/health informatics venues
  • Excellent written and oral communication skills
  • Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory
  • Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs

Benefits at ORNL:

ORNL offers competitive pay and benefits programs to attract and retain talented people. The laboratory offers many employee benefits, including medical and retirement plans and flexible work hours, to help you and your family live happy and healthy. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also provided for convenience.

Other benefits include: 

Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.

 

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.

To apply for this job please visit jobs.ornl.gov.