MSE Tenure-Track Positions

Location: Philadelphia, PA

Open Date: Oct 13, 2026

Deadline:

The Department of Materials Science and Engineering at the University of Pennsylvania is conducting a multi-year search fortenure-track faculty whose research aligns with the strategic plan of the School of Engineering and Applied Science (Penn Engineering).

We invite applications from all experimental and computationalareas of materials research. We have particular interest in candidates who develop or apply emerging methods in artificial intelligence (AI), machine learning (ML), data science, and materials computation. We are interested in these methods as toolsto advance the discovery, synthesis, characterization, and production of electronic materials, structural materials, and materials that address challenges in energy and environmentalsustainability. Penn has signature initiatives in data science, energy and sustainability, and quantum devices and engineering (QUIEST).

Pennalso has shared facilities at the Singh Center for Nanotechnology, the Vagelos Laboratory for Energy Science and Technology (VLEST), and the Laboratoryfor Research on the Structure of Matter (LRSM).

We seek colleagues who will help build a collegial scholarlycommunity within the department, across Penn Engineering, and throughout the University. We also seek colleagues who will work closely with students to identify and address researchchallenges.

Penn Engineering strongly supports dual-career couples. We encourage early inquiries about dual-career assistance for both academic and non-academic opportunities.

Progress in materials science and advanced manufacturing depends onthe discovery, development, and characterization of new electronic,structural, sustainable, and energy-related materials systems. Thenext generation of highly engineered materials is expected to besynthesized with control over several features sefeatures are local atomic bonding and structure, anisotropy, the ordering of defects, charges, and spins, and dimensionality andtopology. We seek candidates with experimental or computationalexpertise who develop modern tools that integrate AI, ML, data science, and materials computation to accelerate materials discovery, synthesis, characterization, and processing.

Ofparticular interest are AI/ML and computational approaches tomaterials prediction and design, autonomous experimentation,synthesis and processing, and characterization. This includesmethods that combine physical models, simulation, data, and experiment.

Areas of interest include, but are not limited to:

• Autonomous and AI-driven materials discovery, characterization,optimization, synthesis, and processing
• Data-driven design and synthesis of solid-state materials
• Scalable methods for producing and integrating materials acrossall length scales
• Prediction and control of material composition, structure, and properties at multiple length scales
• Translation of fundamental materials science into electronics,photonics, sensing, and energy applications

The ideal candidate will demonstrate the ability to predict,control, and interrogate material composition, structure, and properties at multiple length scales to enable next-generationdevices and systems. Candidates should have a strong background in materials theory, computation, synthesis, or characterization. They should also have a clear vision for how their approach will improvedevice performance and functionality and accelerate materialsinnovation. We particularly encourage applications from candidates who connect fundamental materials science to device and system performance and who are committed to fostering interdisciplinary collaboration.

Prof. Christopher

B. Murray chairs the search committee. Review of applications will proceed on a rolling basisand candidates are encouraged to submit materials early for full consideration. All application materials must be received by December 1, 2026.

Must have a Ph.D. in Materials Science and Engineering or related disciplines.

Equal Employment Opportunity Statement

The University of Pennsylvania is an equal opportunity employer.

Candidates are considered for employment without regard to race,color, sex, sexual orientation, religion, creed, national origin(including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.