MSE Tenure-Track Positions 2026–2027

University of Pennsylvania • Philadelphia, PA

23h

About The Position

The Department of Materials Science and Engineering at the University of Pennsylvania is conducting a multi-year search for tenure-track faculty whose research aligns with Penn Engineering’s strategic plan. The department invites applications from experimental and computational areas of materials research, with particular interest in candidates developing or applying artificial intelligence, machine learning, data science, and materials computation to advance the discovery, synthesis, characterization, and production of electronic, structural, energy-related, and sustainable materials.

The search focuses on materials discovery, synthesis, and characterization for advanced applications. The department seeks candidates using modern experimental or computational tools to accelerate materials discovery, synthesis, characterization, and processing, including approaches that combine physical models, simulation, data, and experiment. Areas of interest include autonomous and AI-driven materials research; data-driven design and synthesis of solid-state materials; scalable production and integration across length scales; prediction and control of composition, structure, and properties; and translating fundamental materials science into electronics, photonics, sensing, and energy applications.

The ideal candidate can predict, control, and interrogate material composition, structure, and properties at multiple length scales to enable next-generation devices and systems. Candidates should bring a strong background in materials theory, computation, synthesis, or characterization and a clear vision for improving device performance and functionality and accelerating materials innovation. The department seeks colleagues who will contribute to a collegial scholarly community, work closely with students on research challenges, and foster interdisciplinary collaboration. Penn Engineering supports dual-career couples and encourages early inquiries about assistance for academic and non-academic opportunities.

Applications are reviewed on a rolling basis, and candidates are encouraged to submit materials early. All application materials must be received by December 1, 2026.

Requirements

• Ph.D. in Materials Science and Engineering or a related discipline.
• Strong background in materials theory, computation, synthesis, or characterization.
• Clear vision for how the candidate’s approach will improve device performance and functionality and accelerate materials innovation.

Nice To Haves

• Expertise developing or applying AI, machine learning, data science, or materials computation methods.
• Research connecting fundamental materials science to device and system performance.
• Expertise in autonomous and AI-driven materials discovery, characterization, optimization, synthesis, or processing; data-driven design and synthesis of solid-state materials; scalable production and integration of materials across length scales; or prediction and control of material composition, structure, and properties across length scales.
• Commitment to fostering interdisciplinary collaboration.

Responsibilities

• Conduct research in experimental or computational materials science and engineering aligned with the strategic plan of Penn Engineering.
• Develop or apply emerging AI, machine learning, data science, and materials computation methods to advance materials discovery, synthesis, characterization, production, or processing.
• Contribute to a collegial scholarly community within the department, across Penn Engineering, and throughout the University.
• Work closely with students to identify and address research challenges.
• Foster interdisciplinary collaboration and connect fundamental materials science to device and system performance.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree