Postdoctoral Research Associate - Computational Materials Scientist for Structural Lightweight Alloy

Oak Ridge National Laboratory - Oak Ridge, TN

Full-time - Entry Level

Oak Ridge, TN

5,001-10,000 employees

Professional, Scientific, and Technical Services

About the position

The Postdoctoral Research Associate position at Oak Ridge National Laboratory focuses on utilizing Integrated Computational Materials Engineering (ICME) approaches, machine learning (ML), and artificial intelligence (AI) to advance the discovery and design of structural alloys. The role emphasizes collaboration with experimentalists to create a feedback loop between computational predictions and experimental validation, aiming to develop next-generation alloys with enhanced performance.

Responsibilities

• Conduct alloy research using computational thermodynamics, focusing on high-throughput computations integrated with data analytics for alloy discovery and design.
• Work with members of dynamic research groups to develop theoretical approaches to support the development of next generation high-temperature materials for harsh environments.
• Present and report research findings and publish scientific results in peer-reviewed journals in a timely manner.
• Maintain a strong dedication to the implementation and perpetuation of values and ethics of the institution.
• Align behaviors, priorities, and interactions with ORNL's core values of Impact, Integrity, Teamwork, Safety, and Service, while promoting diversity, equity, inclusion, and accessibility.

Requirements

• A PhD in Materials Science & Engineering, Physics, Chemistry, or a related field completed within the last 5 years.
• A minimum of two years of experience utilizing computational thermodynamic (CALPHAD) software, such as Thermo-Calc, DICTRA, PANDAT, or FactSage.
• Proficiency in materials data analytics, including correlation analysis and machine learning techniques.

Nice-to-haves

• Comprehensive understanding of ICME.
• A strong record of publications in peer-reviewed journals to demonstrate research productivity and creativity.
• Proven expertise in kinetic and microstructural modeling, with demonstrated experience in developing and applying simulation tools to predict microstructural evolution and phase transformations.
• Strong background in atomistic simulations, such as density functional theory (DFT) and/or molecular dynamics (MD), with a preference for experience leveraging high-performance computing (HPC) platforms to perform large-scale simulations.
• 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

• Competitive salary and benefits package.
• Opportunities for professional development and training.
• Access to state-of-the-art research facilities and resources.