MSE Tenure-Track Positions 2026-2027

MSE Tenure-Track Positions 2026–2027

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 for
tenure-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 computational
areas 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 tools
to advance the discovery, synthesis, characterization, and
production of electronic materials, structural materials, and
materials that address challenges in energy and environmental
sustainability. Penn has signature initiatives in data science, energy and sustainability, and
quantum devices and engineering (QUIEST). Penn
also has shared facilities at the Singh Center for
Nanotechnology, the Vagelos
Laboratory for Energy Science and Technology (VLEST), and the
Laboratory
for Research on the Structure of Matter (LRSM).

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

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

Materials Discovery, Synthesis, and Characterization for
Advanced Applications

Progress in materials science and advanced manufacturing depends on
the discovery, development, and characterization of new electronic,
structural, sustainable, and energy-related materials systems. The
next generation of highly engineered materials is expected to be
synthesized with control over several features at once. These
features are local atomic bonding and structure, anisotropy, the
ordering of defects, charges, and spins, and dimensionality and
topology. We seek candidates with experimental or computational
expertise who develop modern tools that integrate AI, ML, data
science, and materials computation to accelerate materials
discovery, synthesis, characterization, and processing. Of
particular interest are AI/ML and computational approaches to
materials prediction and design, autonomous experimentation,
synthesis and processing, and characterization. This includes
methods 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 across

all 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-generation
devices 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 improve
device performance and functionality and accelerate materials
innovation. 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 basis
and candidates are encouraged to submit materials early for full
consideration. All application materials must be received by
December 1, 2026.

Qualifications

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

Application Instructions

Applications must be submitted online via
Interfolio. Applications include:

• Cover Letter
• Curriculum vitae
• Research statement (5-page limit)
• Teaching statement (2-page limit)
• Three confidential letters of recommendation

To apply, visit https://apply.interfolio.com/195553

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.

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