Bioformulation Digital Twin Developer

Johns Hopkins University; Baltimore (MD); On-site; USD 70,000 - 85,000; Full time

Job summary

Johns Hopkins University is seeking a PREP Research Associate to contribute to the NIST FRAME program in Baltimore. The role focuses on developing generative models for soft matter systems, requiring a PhD in relevant fields like machine learning or materials science.

The ideal candidate will possess strong Python skills and a demonstrated ability to conduct independent research. Responsibilities include collaborating with experimental teams and presenting findings at meetings.

Qualifications

• PhD completed by the start date in a relevant field.
• Strong skills with Python and modern machine-learning stacks.
• Demonstrated ability to execute independent research and publish.

Responsibilities

• Develop, train, and validate generative models for soft matter systems.
• Design model architectures and training pipelines.
• Collaborate with experimentalists and present results.

Skills

Python programming

Generative modeling

Machine learning

Collaboration

Scientific data engineering

Education

PhD in machine learning, computer science, physics, chemistry, materials science, chemical engineering, or a related field

Tools

PyTorch

Job description

Johns Hopkins University is seeking a PREP Research Associate to contribute to the NIST FRAME program in Baltimore. The role focuses on developing generative models for soft matter systems, requiring a PhD in relevant fields like machine learning or materials science.

The ideal candidate will possess strong Python skills and a demonstrated ability to conduct independent research. Responsibilities include collaborating with experimental teams and presenting findings at meetings.