Postdoctoral Fellow

Postdoctoral Fellow - Atomistic Simulations and AI for Materials Design

Requisition #: A

Status: Full Time

Type: Post Doc

School: Whiting School of Engineering

Department/Program: Department of Materials Science and Engineering

Salary: $62,232 - $75,564

Location City: Baltimore

Location State: MD

Location Zip Code: 21218

Closing Date: Open until filled

To apply:

General Description

The AtomGPTLab, led by Dr. Kamal Choudhary at Johns Hopkins University, invites applications for a Postdoctoral Fellow position in the fields of atomistic simulations, machine-learned force fields, and artificial intelligence (AI). The successful candidate will lead the development of a computational platform that unifies first-principles methods, classical molecular simulations, and cutting-edge AI techniques including graph neural networks (GNNs) and large language models (LLMs) to accelerate experimental design and discovery of novel materials.

The research spans quantum mechanics, statistical physics, and deep learning, and aims to enable AI-guided predictions of synthesizable and functional materials such as superconductors, catalysts, semiconductors, and energy-relevant compounds. The position is embedded in an interdisciplinary and collaborative environment with active interactions across experimental groups and national laboratories.

Qualifications

Basic Qualifications or Specialized Certifications

• A PhD in Materials Science, Physics, Chemistry, Chemical Engineering, Computer Science, or a related field.

• Demonstrated experience in one or more of the following: Density Functional Theory (DFT), machine-learned force fields (MLFF), graph neural networks (GNNs), or large language models (LLMs).

Extensive Knowledge In:

• First-principles simulations with packages such as VASP, Quantum ESPRESSO, GPAW.

• Machine-learned interatomic potentials (e.g., ALIGNN-FF).

• Structure-property prediction using GNNs (e.g., ALIGNN,).

• LLM fine-tuning and prompt engineering (e.g., HuggingFace, OpenAI, AtomGPT).

Working Knowledge Of:

• Workflow tools (e.g.,JARVIS-Tools, ASE) and HPC environments.

• Software development in Python, Git-based version control, and Conda packaging.

• Data integration and surrogate modeling using experimental and computational datasets.

• Interdisciplinary collaboration and mentoring of students or junior researchers.

Specific Duties & Responsibilities

• Conduct high-throughput DFT calculations and manage large-scale materials datasets.

• Develop GNN architectures for predicting materials properties from atomic graphs.

• Train and deploy machine-learned force fields for MD simulations and rapid screening.

• Fine-tune or pre-train LLMs for generation and analysis of materials structures, synthesis protocols, and characterization outputs.

• Build pipelines for combining experimental and simulated data for inverse design.

• Provide real-time computational feedback to experimental collaborators for synthesis and characterization.

• Lead manuscript writing, conference presentations, and contributions to open-source repositories.

• Mentor undergraduate and graduate students, and participate in grant proposal development.

Additional Opportunities

• Collaborate as Co-PI on interdisciplinary proposals.

• Engage with experimental groups, national labs, and industry partners.

• Participate in the development of open cyberinfrastructure (e.g., ).

• Attend international conferences and contribute to global research communities.

• Access to cutting-edge computing clusters and experimental characterization tools.

Application Instructions

Applicants should submit a curriculum vitae and three recent publications. Review of applications will begin in mid-August 2025.

To apply for this position, visit:

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:

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 characteristic. 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 that are irrelevant to the program involved.

Pre-Employment Information

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Background Checks

The successful candidate(s) for this position will be subject to a pre-employment background check including education verification.

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Diversity and Inclusion

The Johns Hopkins University values diversity, equity and inclusion and advances these through our key strategic framework, the JHU Roadmap on Diversity and Inclusion.

Vaccine Requirements

Johns Hopkins University strongly encourages, but no longer requires, at least one dose of the COVID-19 vaccine. The COVID-19 vaccine does not apply to positions located in the State of Florida. We still require all faculty, staff, and students to receive the seasonal flu vaccine. Exceptions to the COVID and flu vaccine requirements may be provided to individuals for religious beliefs or medical reasons. Requests for an exception must be submitted to the JHU vaccination registry. This change does not apply to the School of Medicine (SOM). SOM hires must be fully vaccinated with an FDA COVID-19 vaccination and provide proof of vaccination status. For additional information, applicants for SOM positions should visit and all other JHU applicants should visit

The following additional provisions may apply, depending upon campus. Your recruiter will advise accordingly. The pre-employment physical for positions in clinical areas, laboratories, working with research subjects, or involving community contact requires documentation of immune status against Rubella (German measles), Rubeola (Measles), Mumps, Varicella (chickenpox), Hepatitis B and documentation of having received the Tdap (Tetanus, diphtheria, pertussis) vaccination. This may include documentation of having two (2) MMR vaccines; two (2) Varicella vaccines; or antibody status to these diseases from laboratory testing. Blood tests for immunities to these diseases are ordinarily included in the pre-employment physical exam except for those employees who provide results of blood tests or immunization documentation from their own health care providers. Any vaccinations required for these diseases will be given at no cost in our Occupational Health office.