Description
POSTDOCTORAL RESEARCH ASSOCIATE – Interpretable DNA/RNA Ensemble Quantification (molecular dynamics, machine learning, measurement analysis).
Biophysical and Biomedical Measurement Group (Microsystems and Nanotechnology Division)
National Institute of Standards and Technology (NIST) – Gaithersburg, MD
The Biophysical and Biomedical Measurement Group at NIST (Gaithersburg, MD) is seeking a postdoctoral research associate to advance a theory/computation project focused on classifying DNA and RNA ensembles using secondary-structure-based distance metrics and clustering.
A central goal is to build hierarchical, interpretable ensemble representations that connect simulation-derived clusters to experimental measurements/observables and statistical-physics interpretation (e.g., energetic barriers and kinetic pathways).
Related paper: Clustering DNA and RNA molecular dynamics ensembles via secondary structure
https://doi.org/10.1016/j.bpj.2025.08.029
What you will do:
- Develop, test, and extend secondary-structure representations for DNA/RNA derived from molecular dynamics (MD) trajectories or experiment
- Implement and optimize secondary-structure distance metrics based on base-pair reorganization, with careful handling
of topology assumptions (e.g., consistent knot topology within clusters; extensions/generalizations to knotted and/or
pseudoknotted structures as necessary)
- Build scalable clustering and model-selection workflows for large MD datasets (e.g., k-means, hierarchical clustering,
density-based clustering) and evaluate robustness (e.g., stability analyses and other diagnostics)
- Analyze large nucleic-acid MD datasets via trajectory coarse-graining and secondary-structure time series; connect
clustering outputs to kinetics and free-energy landscape interpretation, including energetic barriers relevant to
hybridization disruption/reorganization
- Develop well-documented, reproducible research software (version control, testing, packaging, interfaces) and
publish/present results
- Collaborate with experimental and device-focused teams to connect theory outputs to measurement needs
Requirements
Required qualifications (please be specific in your application about these):
- Ph.D. in physics, chemistry, biophysics, computational biology, applied mathematics, computer science, or a closely
related field
- Demonstrated experience with biomolecular simulation and/or trajectory analysis (strong preference for nucleic acids:
DNA/RNA)
- Experience with coarse-grained nucleic-acid models, e.g., oxDNA/oxRNA or closely related CG frameworks
- Strong scientific programming (Python expected; NumPy/SciPy; data handling; plotting; performance optimization) and
ability to write maintainable, version-controlled code
- Practical understanding of clustering/unsupervised learning and distance-metric design, including how choices affect
outcomes and validation/robustness
- Strong communication skills (written and oral)
Highly desired (one or more):
- Experience extracting secondary structure from 3D structures/MD (base-pair detection, hydrogen-bond criteria, contact
maps; secondary-structure time series)
- Experience with MD packages and analysis tools (e.g., LAMMPS/NAMD/GROMACS and related)
- High-performance computing experience (batch systems; parallel processing; profiling/optimization)
- Background in statistical mechanics / polymer physics / stochastic processes; free-energy or kinetic modeling of
conformational ensembles
- Experience analyzing experimental data from single-molecule and ensemble techniques
U.S. citizenship is preferred; for some appointment mechanisms, eligibility depends on citizenship.
To apply:
Email (i) a CV, (ii) a brief statement describing your technical fit for this specific project (please highlight relevant methods/tools and your role in developing or applying them), and (iii) names/contact info for 2–3 references.
NRC pathway (U.S. citizens):
NRC Research Associateship Programs (RAP) opportunity “Theoretical Nanoscale Biophysics”
Group information:
https://www.nist.gov/pml/microsystems-and-nanotechnology-division/biophysical-and-biomedical-measurement-group
