Postdoctoral Fellow (PREP0004514)

Johns Hopkins University; Baltimore (MD); On-site; USD 70,000 - 90,000; Full time

Benefits offered by this job

Health and life benefits

Career development resources

Retirement support

Job summary

Johns Hopkins University seeks a PREP Research Associate in Baltimore, MD, focusing on DNA/RNA ensemble quantification and molecular dynamics. This role involves developing algorithms and producing reproducible research software, contributing to significant scientific collaborations.

The ideal candidate will have a Ph.D. and experience in biomolecular simulations, with strong programming abilities in Python. This position is part of a team where communication and collaboration are key to success.

Qualifications

• Ph.D. in a relevant field, preferably related to biology or computational science.
• Experience with biomolecular simulation and trajectory analysis required.
• Programming skills in Python or Julia and ability to maintain version-controlled code.

Responsibilities

• Develop and optimize distance metrics based on base-pair reorganization.
• Implement clustering and model-selection for molecular dynamics datasets.
• Present research findings at conferences and meetings.

Skills

Biomolecular simulation experience

Strong scientific programming (Python preferred)

Understanding of clustering/unsupervised learning

Statistics/statistical physics background

Strong written and oral communication skills

Education

Ph.D. in physics, chemistry, biophysics, computational biology, applied mathematics, computer science

Tools

Python

Julia

Job description

PREP Research Associate

This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.

Research Title

Interpretable DNA/RNA Ensemble Quantification (Molecular dynamics, machine learning, measurement analysis)

Work Focus

This position will focus on theory and computation to classify DNA and RNA conformational 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). Work includes developing and validating analysis algorithms, implementing reproducible research software, and collaborating with experimental and device‑focused teams to connect theory outputs to measurement needs.

Key Responsibilities

• Develop, test, and extend ensemble representations for DNA/RNA and relate these to experimental observables.
• Implement and optimize secondary‑structure distance metrics based on base‑pair reorganization.
• Build scalable clustering and model‑selection for large molecular dynamics datasets.
• Present results at internal and external meetings and conferences.
• Develop well‑documented, reproducible research software and publish results.

Qualifications

• A 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 coarse‑grained frameworks.
• Practical understanding of clustering/unsupervised learning and distance‑metric design.
• Strong scientific programming (Python preferred; Julia a plus) and ability to write maintainable, version‑controlled code.
• Background in statistics/statistical physics; ability to interpret ensembles in terms of kinetics and free‑energy landscapes.
• Strong written and oral communication skills and ability to collaborate in a multidisciplinary team; experience analyzing experimental data from single‑molecule and ensemble techniques is a plus.

Preferred

U.S. Citizen Preferred.

Salary Range

The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.

Total Rewards

Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: https://hr.jhu.edu/benefits-worklife/.

Equal Opportunity Employer

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristics. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors or demographic characteristics that are irrelevant to the program involved.