BlueHalo has an opportunity available for a research scientist to join our multidisciplinary team at the Air Force Research Laboratory (AFRL) and contribute to cutting-edge research at the intersection of materials science, computational physics, and machine learning.

The successful candidate will conduct research as an active member of the computational polymer physics research team within the Materials and Manufacturing Directorate at the Air Force Research Laboratory (AFRL).  The research project will focus on understanding and predicting the complex phase behavior of multicomponent polymer solutions and blends using a combination of polymer physics, phase-field modeling, and machine learning.  The successful candidate will leverage advanced machine learning techniques (theory-informed ML, graph neural networks, etc.) to develop predictive models for phase diagrams and kinetic pathways, coupled with phase-field simulations to explore the microstructure evolution at various times and length scales.  The goal is to accelerate the design and development of novel polymer materials with tailored properties for DAF applications.  The position will work closely with AFRL scientists as well as professors, students, staff, and industry collaborators.

 

Excellent oral and written communication skills are a prerequisite for employment.  The successful candidate will be self-motivated and capable of working independently, but also collaborate with researchers from different technical backgrounds.  Applications will be reviewed until the position is filled.

• Ph.D. (with 0-1 year of experience) in Polymer Science, Chemical Engineering, Materials Science, Physics, or a closely related field.
• Proven experience in numerical methods and simulations, preferably with phase-field modeling.
• Proficiency in at least one programming language (e.g., Python, C++, MATLAB) and experience with machine learning frameworks (e.g., TensorFlow, PyTorch).
• Excellent analytical, problem-solving, and communication skills.
• Ability to work independently and collaboratively within a team.
• This position is working within a government facility and requires US Citizenship

Preferred Education and Experience:

• Strong background in polymer physics and thermodynamics, including an understanding of polymer solution theory, phase transitions, and polymer morphology.
• Familiarity with statistical mechanics and advanced computational techniques.
• Publication record in peer-reviewed journals.
• Experience with high-performance computing.

None

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