Postdoctoral Fellow in Atomistic Simulations and AI for Materials Design

Laplace Expert Ltd; Maryland; In loco; USD 60.000 - 80.000; Tempo pieno

Descrizione del lavoro

Johns Hopkins University in Maryland invites applications for a Postdoctoral Fellow in atomistic simulations and AI for materials design. The role emphasizes DFT, machine-learned force fields, graph neural networks and large language models to accelerate materials discovery.

The AtomGPTLab will build a computational platform integrating first-principles methods, molecular simulations, GNNs and LLMs to enable faster experimental design, data integration, open-source contributions, mentoring and

Competenze

• Ph.D. in Materials Science, Physics, Chemistry, Chemical Engineering, Computer Science or related field is required.
• Experience in at least one of density functional theory, machine-learned force fields, graph neural networks or large language models.

Mansioni

• Lead high-throughput DFT studies and develop machine-learned force fields.
• Develop graph neural networks and large language models for materials design.
• Contribute open-source software, mentor students, and prepare manuscripts.
• Collaborate across disciplines to accelerate materials discovery.

Conoscenze

Interdisciplinary collaboration

Mentoring

Manuscript writing

Grant proposal contribution

Scientific communication

Formazione

Ph.D. in Materials Science/Physics/Chemistry/Chemical Engineering/Computer Science or related field

Strumenti

Density functional theory

Machine-learned force fields

Graph neural networks

Large language models

VASP

Quantum ESPRESSO

GPAW

ALIGNN-FF

ALIGNN

HuggingFace

OpenAI

AtomGPT

JARVIS-Tools

ASE

High-performance computing

Python

Git

Conda packaging

Surrogate modeling

Graph neural networks

Large language models

Descrizione del lavoro

Postdoctoral Fellow in Atomistic Simulations and AI for Materials Design

Johns Hopkins University

Maryland

Not specified

About This Opportunity

Johns Hopkins University is recruiting a Postdoctoral Fellow in atomistic simulations and AI for materials design. The role focuses on DFT, machine-learned force fields, graph neural networks and large language models for materials discovery.

The AtomGPTLab at Johns Hopkins University is recruiting a postdoctoral fellow in atomistic simulations, machine-learned force fields and artificial intelligence. The researcher will help build a computational platform that integrates first-principles methods, molecular simulations, graph neural networks and large language models to accelerate experimental design and discovery of functional materials. The role includes high-throughput DFT, model development, data integration, open-source contributions, mentoring and manuscript preparation.

Atomistic Simulation and AI for Materials Design Materials Science

Level Postdoc

Field Atomistic Simulation and AI for Materials Design

Organization Type University

Funding & Compensation

Amount Paid

Funding Type Salary

Funding Status Paid

Requirements

Education

Applicants must hold a Ph.D. in Materials Science, Physics, Chemistry, Chemical Engineering, Computer Science or a related field.

Experience

Applicants must demonstrate experience in at least one of density functional theory, machine-learned force fields, graph neural networks or large language models.

Technical Skills

• Density functional theory
• Machine-learned force fields
• Graph neural networks
• Large language models
• VASP
• Quantum ESPRESSO
• GPAW
• ALIGNN-FF
• ALIGNN
• HuggingFace
• OpenAI
• AtomGPT
• JARVIS-Tools
• ASE
• High-performance computing
• Python
• Git
• Conda packaging
• Surrogate modeling

General Skills

• Interdisciplinary collaboration
• Mentoring
• Manuscript writing
• Grant proposal contribution
• Scientific communication