Postdoctoral Research Associate - Computational Chemistry

Oak Ridge National Laboratory; Oak Ridge (TN); On-site; USD 65,000 - 90,000; Full time

Job summary

Oak Ridge National Laboratory (ORNL) seeks a Postdoctoral Research Associate focused on developing and applying machine learning interatomic potentials (MLIPs) and free energy methods to ion separations and energy-related processes. The role involves MD simulations with MLIPs and collaboration across theory, spectroscopy, synthesis, and separations.

You will work in the Chemical Separations Group to advance understanding of ions binding, transfer across interfaces, and the design of chelating

Qualifications

• PhD in theoretical or computational chemistry completed within the last 5 years.
• Experience with density functional theory (DFT) and/or molecular dynamics (MD) simulations using ab initio and machine learning potentials.
• Experience in employing advanced statistical mechanics methods for simulations of materials.

Responsibilities

• Develop, fine-tune, validate, and deploy MLIPs, including MACE or related architectures for ions and ligands in single and two-phase separation systems.
• Conduct molecular dynamics with MLIPs using LAMMPS, OpenMM, or comparable software to study thermodynamics and structure of binding and separation.
• Calculate ion solvation, ligand binding, and complexation free energies using thermodynamic integration and related methods.
• Investigate ion transport and proton transfer at liquid interfaces; relate interfacial structure to transfer free energies.
• Present and publish research results in peer-reviewed journals in a timely manner.

Skills

DFT methods

MD simulations

Machine learning potentials

Ab initio calculations

Statistical mechanics

Education

PhD in theoretical/computational chemistry

Tools

VASP

Gaussian

Orca

LAMMPS

OpenMM

CP2K

Psi4

Job description

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Postdoctoral Research Associate - Computational Chemistry

We are seeking a Postdoctoral Research Associate who will focus on developing and applying machine learning interatomic potentials (MLIPs) and free energy methods to ion separations, interfacial science, and energy-related processes. This position resides in the Chemical Separations Group in the Separations and Polymer Section, Chemical Sciences Division, Physical Sciences Directorate, at Oak Ridge National Laboratory (ORNL). In this role, you will develop and/or fine-tune MLIPs using ab initio calculations and run molecular dynamics simulations to understand the thermodynamics of ion complexation in the bulk and transfer across liquid-liquid interfaces. You will also work within a multidisciplinary multi-institutional team involving specialists in theory, spectroscopy, organic synthesis, and separations.

Major Duties/Responsibilities:

• Work with a diverse team of scientists seeking to advance scientific understanding of structural and energetic aspects of ions binding and separation
• Develop, fine-tune, validate, and deploy MLIPs, including MACE or related architectures and foundation models, for ions and ligands in single and two-phase separation systems
• Conduct molecular dynamics with MLIPs using LAMMPS, OpenMM, or comparable simulation software to elucidate the thermodynamic and structural basis of enhanced binding and selectivity manifested in improved separations
• Calculate ion solvation, ligand binding, and complexation free energies using thermodynamic integration and related methods; quantify uncertainty and assess convergence
• Investigate ion transport and proton transfer at liquid interfaces; elucidate how interfacial structure and solvent organization affect reaction and transfer free energies
• Independently plan and conduct simulations and work with experimentalists to help interpret experimental results and guide the design of new chelating agents
• Present and report research results and publish scientific results in peer-reviewed journals in a timely manner
• 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.

Basic Qualifications:

• A PhD in theoretical or computational chemistry or closely related field in physical chemistry or chemical physics completed within the last 5 years
• Experience with density functional theory (DFT) (e.g., VASP, Gaussian, Orca) and/or molecular dynamics (MD) simulations using ab initio and machine learning potentials (e.g., LAMMPS, OpenMM, CP2K, Psi4)
• Experience in employing advanced statistical mechanics methods for simulations of materials (e.g., thermodynamic integration)

Preferred Qualifications:

• Experience with Message Passing Atomic Cluster Expansion (MACE) or related equivariant MLIPs, foundation models, transfer learning, fine-tuning, or active learning
• Background in molecular simulations of ions in liquids, including the treatment of long-range electrostatics and polarization
• Demonstrated ability to compute free energies by thermodynamic integration, free energy perturbation, MBAR, umbrella sampling, or related approaches
• Proficiency in applying electronic structure methods and running parallel calculations on high-performance computing systems
• Familiarity with electronic structure methods for excited states
• Excellent record of productive and creative research as demonstrated by publications in peer-reviewed journals
• 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.

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.

About ORNL:

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation's most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.

Other benefits include the following: 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.

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.