Postdoctoral Associate: Unsupervised Learning for DNA/RNA Molecular Dynamics

Interpretable DNA/RNA Ensemble Quantification (molecular dynamics, machine learning, clustering, and 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

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

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.

Contact:
Dr. Michael Zwolak ( View email address on nature.com )

NRC pathway (U.S. citizens):
NRC Research Associateship Programs (RAP) opportunity “Theoretical Nanoscale Biophysics”

Group information:

NIST Overview:

The National Institute of Standards and Technology (NIST) is a US federal government laboratory tasked to promote U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve our quality of life. The NIST Laboratories conduct world-class research, often in close collaboration with industry, that advances the nation's technology infrastructure and helps U.S. companies continually improve products and services; The agency operates in two locations: Gaithersburg, Md., (headquarters—234-hectare/578-acre campus) and Boulder, Colo., (84-hectare/208-acre campus). NIST employs about 3,400 scientists, engineers, technicians, and support and administrative personnel. NIST also hosts about 3,800 associates from academia, industry, and other government agencies, who collaborate with NIST staff and access user facilities. In addition, NIST partners more than 1,300 manufacturing specialists and staff at more than 400 MEP service locations around the country. NIST is an Equal Opportunity Employer.