GenAI Materials Discovery Postdoc (Onsite)

Sandia National Laboratories; Albuquerque (NM); In loco; USD 65.000 - 90.000; Tempo pieno

Vantaggi offerti da questo lavoro

Flexible work arrangements

Telecommuting options

Descrizione del lavoro

Sandia National Laboratories in Albuquerque, NM invites applications for a Postdoctoral Appointee in the Materials Lifecycle Management Department. You will apply electronic structure calculations and machine learning to accelerate materials discovery and characterization, collaborating with a multi-disciplinary team.

Strong publication record and the ability to obtain a DOE Q-Clearance are required. This onsite role offers mentorship, training, and opportunities to work with national labs,

Competenze

• PhD in Material Science, Engineering, Applied Mathematics, Physics, Chemistry, Bioinformatics, Computer Science, Machine Learning, Artificial Intelligence, or related field with emphasis on building, evaluating, and applying predictive models.
• Familiarity with interpretable machine learning techniques to discover structure-function relationships.
• Record of technical accomplishment and written communication evidenced by publication in high-impact journals.
• Ability to obtain and maintain a DOE Q-Clearance.

Mansioni

• Apply electronic structure calculations, machine learning, and/or first principles simulations to accelerate materials discovery and characterization.
• Integrate outputs of machine learning models with physics-based models or classical simulations to predict properties.
• Mentor technologists and interns; collaborate with national labs, universities, and industry.
• Communicate research through papers, peer-reviewed journals, and presentations at seminars/conferences.
• Execute, monitor, and refine project plans and proposals.

Conoscenze

Interpretable ML

Publications in high-impact journals

PhD background

Formazione

PhD in Material Science / Engineering / Physics

Descrizione del lavoro

Sandia National Laboratories in Albuquerque, NM invites applications for a Postdoctoral Appointee in the Materials Lifecycle Management Department. You will apply electronic structure calculations and machine learning to accelerate materials discovery and characterization, collaborating with a multi-disciplinary team.

Strong publication record and the ability to obtain a DOE Q-Clearance are required. This onsite role offers mentorship, training, and opportunities to work with national labs,