BASIC QUALIFICATIONS:

• A Ph.D. in computer science, computational science, data science, artificial intelligence, or related field completed within the last 5 years or to be expected in 2025.
• Demonstrated experience working with machine learning and data analytics using tools in programming languages such as Python, PyTorch, Pandas, Scikit Learn, etc., in applied problem-solving contexts.
• Understanding of machine learning algorithms (gradient descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers).
• A broad understanding of machine learning methodologies and data science methodologies and techniques, (e.g. supervised and unsupervised learning, feature selection/engineering, hyperparameter optimization, dimensionality reduction, embeddings, etc.)
• Understanding of computational scaling techniques for machine learning and high-performance computing

PREFERRED QUALIFICATIONS:

• A strong publication record demonstrating either core machine learning capabilities or novel applications of machine learning.
• Expertise in deep learning techniques such as transformers, LLM, GNN, generative models OR advance matrix method such as matrix/tensor completion, non-negative factorization OR anomaly detection
• Excellent written and oral communication skills
• Ability to work independently and to participate creatively in collaborative teams across the laboratory.
• Ability to set priorities to accomplish multiple tasks within deadlines and adapt to changing needs.

SPECIAL REQUIREMENTS:

Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.
Please submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent to recruiting@ornl.gov with the position title and number referenced in the subject line.

Instructions to upload documents to your candidate profile:

• Login to your account via jobs.ornl.gov
• View Profile
• Under the My Documents section, select Add a Document

• Conduct independent and collaborative research in the general areas of AI for science, focusing on high-impact scientific problems
• Apply state-of-the-art AI techniques in high-impact application areas such as small molecule drugs, materials, and other application domains
• Collaborate with regulatory agencies to develop solutions that support decision-making processes.
• Build strong collaborations within ORNL and across the global research community.
• Publish groundbreaking research in top-tier machine learning conferences and journals.
• Be a part of a collaborative research environment which will provide the opportunity to perform cutting-edge research in deep learning and scientific computing.
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.