AI-Enabled Critical Materials & Circular Manufacturing — Tenure-Track

University of Missouri-Kansas City; Kansas City (MO); Vor Ort; USD 90.000 - 120.000; Vollzeit

Zusammenfassung

UMKC invites applications for a tenure-track Assistant Professor whose research uses artificial intelligence, data, sensing, automation, and systems engineering to accelerate the translation and manufacture of critical materials. This is not intended as a generic AI search.

The candidate’s methods must be anchored in materials processing, manufacturing, recycling, or qualification. Potential areas include: digital twins for critical-material processing and manufacturing, AI-assisted separation,

Qualifikationen

• Doctorate in engineering, computer science, data science, applied mathematics, materials science, chemistry, or a closely related field.
• evidence of excellent research potential.
• a clear plan for an externally funded program at the intersection of intelligent systems and critical-material translation.
• commitment to teaching and mentoring.

Aufgaben

• Develop an externally funded translational research program.
• Collaborate with materials scientists, chemists, engineers, computer scientists, statisticians, and industry partners.
• Apply AI and computational methods to real processing and manufacturing environments.
• Produce scholarly outputs and experimentally or industrially validated technologies.
• Contribute to CMC projects, shared research infrastructure, and regional industry partnerships.
• Mentor students and teach courses in an appropriate SSE program.

Ausbildung

Doctorate in engineering, computer science, data science, applied mathematics, materials science, chemistry, or a closely related field

Jobbeschreibung

UMKC invites applications for a tenure-track Assistant Professor whose research uses artificial intelligence, data, sensing, automation, and systems engineering to accelerate the translation and manufacture of critical materials. This is not intended as a generic AI search.

The candidate’s methods must be anchored in materials processing, manufacturing, recycling, or qualification. Potential areas include: digital twins for critical-material processing and manufacturing, AI-assisted separation,