Postdoctoral Research Associate, Atomistic Simulations & AI-Driven Molecular Modeling

Requisition Id 16217 

­­Overview:  

The Multiscale Biomedical Systems Group within the Advanced Computing in Health (ACH) section of the Computational Sciences and Engineering Division (CSED) at Oak Ridge National Laboratory (ORNL) seeks a motivated Postdoctoral Research Associate.

 

This position primarily focuses on large-scale molecular dynamics (MD) simulations and AI-integrated multiscale modeling of complex biosystems. The successful candidate will also contribute to efforts that bridge molecular, cellular, and systems-level modeling, with growing relevance to emerging paradigms such as whole-cell modeling and networked biological systems.

 

You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing resources and collaborating across ORNL, federal agencies, and academic partners.

 

Key Responsibilities:

• Develop and apply scalable molecular dynamics (MD) and multiscale simulation workflows for biomolecular systems (proteins, enzymes, membranes, and complexes)
• Integrate AI/ML approaches with physics-based simulations to accelerate discovery and improve predictive fidelity
• Contribute to cross-scale modeling frameworks linking molecular interactions to cellular and network-level behavior (e.g. protein-protein interaction, PPI, network analysis)
• Optimize simulation codes and workflows for leadership-class HPC architectures
• Collaborate across interdisciplinary teams spanning biology, chemistry, computer science, and applied mathematics
• Publish findings in high-impact journals and present at leading conferences

 

Required Qualifications:

• Ph.D. (within 0–5 years) in computational bioscience, computational biophysics, computer science, or a related field
• Strong programming skills in C++, Python, or similar scientific computing languages
• Hands-on experience with MD simulation tools such as NAMD, GROMACS, AMBER, or LAMMPS, and visualization tools (e.g., VMD, PyMOL)
• Experience working on high-performance computing (HPC) systems
• Demonstrated ability to conduct independent research with a good publication record
• Excellent written and verbal communication skills for interdisciplinary collaboration
• Commitment to ORNL’s core values: Impact, Integrity, Teamwork, Safety, and Service

 

Preferred Qualifications:

• Deep expertise in atomistic and multiscale simulation methods (e.g., MD, enhanced sampling, QM/MM)
• Experience improving performance and scalability of simulation workflows via:
• Parallelization and performance engineering
• GPU/accelerator optimization
• Algorithmic innovation
• Experience applying machine learning or AI to molecular simulation, including:
• Surrogate models or learned potentials
• Generative models for biomolecular design
• Representation learning for biomolecular systems
• Familiarity with protein–protein interaction (PPI) networks, signaling pathways, or systems biology models (bioinformatics tools and models)
• Experience with integrated multiscale modeling frameworks connecting molecular dynamics to cellular or tissue-scale processes
• Experience with deep learning frameworks such as PyTorch or TensorFlow
• Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving foundation models or scientific LLMs

 

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.

 

Security, Credentialing, and Eligibility Requirements:

For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required.  A