MSE Tenure-Track Positions 2026-2027

University of Pennsylvania; United (PA); On-site; USD 90,000 - 150,000; Full time

Job summary

The Department of Materials Science and Engineering at the University of Pennsylvania invites applications for tenure-track faculty whose research aligns with Penn Engineering's strategic plan.

We welcome candidates from experimental or computational materials research who integrate AI/ML, data science, and materials computation to advance discovery, synthesis, and applications in electronic, structural, sustainable, and energy materials.

Qualifications

• Ph.D. in Materials Science and Engineering or related disciplines.
• Strong background in experimental or computational materials research.
• Ability to integrate AI, ML, data science into materials discovery.

Responsibilities

• Advance tenure-track research aligning with Penn Engineering's strategic plan.
• Collaborate within Penn Engineering and across the university.
• Mentor students and contribute to interdisciplinary collaborations.

Skills

AI/ML in materials

Data science

Materials computation

Education

Ph.D. in Materials Science and Engineering

Job description

MSE Tenure-Track Positions 2026-2027

Location: Philadelphia, PA

Open Date: Oct 13, 2026

Deadline:

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

We invite applications from all experimental and computationalareas of materials research. We have particular interest incandidates who develop or apply emerging methods in artificialintelligence (AI), machine learning (ML), data science, andmaterials computation. We are interested in these methods as toolsto advance the discovery, synthesis, characterization, andproduction of electronic materials, structural materials, andmaterials that address challenges in energy and environmentalsustainability. Penn has signature initiatives in data science, energy and sustainability, andquantum devices and engineering (QUIEST). Pennalso has shared facilities at the Singh Center forNanotechnology, the VagelosLaboratory for Energy Science and Technology (VLEST), and theLaboratoryfor Research on the Structure of Matter (LRSM).

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

Penn Engineering strongly supports dual-career couples. Weencourage early inquiries about dual-career assistance for bothacademic and non-academic opportunities.

Materials Discovery, Synthesis, and Characterization forAdvanced Applications

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 at once. Thesefeatures are local atomic bonding and structure, anisotropy, theordering of defects, charges, and spins, and dimensionality andtopology. We seek candidates with experimental or computationalexpertise who develop modern tools that integrate AI, ML, datascience, and materials computation to accelerate materialsdiscovery, 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, andexperiment.

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, andproperties 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, andproperties at multiple length scales to enable next-generationdevices and systems. Candidates should have a strong background inmaterials theory, computation, synthesis, or characterization. Theyshould also have a clear vision for how their approach will improvedevice performance and functionality and accelerate materialsinnovation. We particularly encourage applications from candidateswho connect fundamental materials science to device and systemperformance and who are committed to fostering interdisciplinarycollaboration.

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

Qualifications

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

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), citizenshipstatus, age, disability, veteran status or any class protectedunder applicable federal, state, or local law.