Research Assistant Scientist

University of Florida•Gainesville, FL

1d•Onsite

About The Position

The Department of Electrical & Computer Engineering in the Herbert Wertheim College of Engineering (HWCOE) at the University of Florida is soliciting applications for a full-time, nine-month, time-limited, non-tenure-track faculty position at the rank of Research Assistant Scientist. The Research Assistant Scientist position will provide strategic leadership in establishing and expanding a nationally recognized, externally funded research program at the intersection of artificial intelligence (AI) and microelectronics failure analysis (FA), inspection, metrology, reliability, and advanced manufacturing. A central expectation is to identify emerging research opportunities and lead the development and submission of competitive proposals to federal agencies, industry sponsors, consortia, and other funding organizations. The successful candidate will define new research thrusts and long-term technical roadmaps; build multidisciplinary proposal teams; and develop sustained collaborations with academic institutions, government agencies, national laboratories, semiconductor manufacturers, equipment vendors, and other industry partners. Research directions may include machine learning (ML), deep learning (DL), large language models (LLMs), vision-language models (VLMs), large multimodal models (LMMs), agentic AI, federated learning (FL), physics-informed AI, and related emerging technologies applied to advanced semiconductor packaging, integrated circuits, printed circuit boards, and broader microelectronics manufacturing and reliability challenges. The position will also provide intellectual and technical leadership for interdisciplinary research programs in AI-enabled microelectronics inspection and failure analysis, with responsibility for guiding projects from concept development and experimental design through model development, validation, deployment, publication, and technology transition. Research may address multimodal defect detection and classification, computational imaging and reconstruction, anomaly detection, automated root-cause analysis, predictive reliability, multimodal data fusion, digital twins, trustworthy and explainable AI, autonomous and agentic inspection systems, and privacy-preserving collaborative learning. Relevant modalities may include X-ray imaging and computed tomography, scanning acoustic microscopy, optical microscopy, infrared and terahertz imaging, SEM/FIB, electrical measurements, and manufacturing or process data. Additional responsibilities include building and mentoring research teams; supervising graduate and undergraduate researchers and research staff; contributing to instruction, curriculum development, seminars, workshops, and workforce-training activities; disseminating research through high-impact publications and technical presentations; advancing intellectual property and technology transfer; and supporting the continued growth, visibility, and research infrastructure of the laboratory and associated academic–government–industry programs.

Requirements

PhD in Electrical Engineering or a closely related field.

Nice To Haves

Demonstrated expertise in AI/ML, including deep learning, computer vision, LLMs, VLMs, multimodal AI, agentic AI, physics-informed AI, or related emerging technologies.
Research experience applying AI to microelectronics, semiconductor manufacturing, advanced packaging, failure analysis, inspection, metrology, reliability, or related engineering challenges.
Experience with multimodal imaging or characterization techniques such as X-ray/CT, scanning acoustic microscopy, optical microscopy, infrared/terahertz imaging, SEM/FIB, or electrical measurements.
Strong record of peer-reviewed publications and demonstrated potential to develop an externally funded research program.
Experience developing proposals and multidisciplinary collaborations with federal agencies, industry, national laboratories, or academic partners.
Experience mentoring graduate and undergraduate researchers and working effectively in interdisciplinary teams.
Familiarity with large-scale multimodal datasets, computational imaging, digital twins, autonomous inspection, or AI-enabled experimental systems is highly desirable.
Demonstrated potential for technology translation, intellectual property development, industry engagement, and workforce training.

Responsibilities

Provide strategic leadership in establishing and expanding a nationally recognized, externally funded research program at the intersection of artificial intelligence (AI) and microelectronics failure analysis (FA), inspection, metrology, reliability, and advanced manufacturing.
Identify emerging research opportunities and lead the development and submission of competitive proposals to federal agencies, industry sponsors, consortia, and other funding organizations.
Define new research thrusts and long-term technical roadmaps.
Build multidisciplinary proposal teams.
Develop sustained collaborations with academic institutions, government agencies, national laboratories, semiconductor manufacturers, equipment vendors, and other industry partners.
Provide intellectual and technical leadership for interdisciplinary research programs in AI-enabled microelectronics inspection and failure analysis.
Guide projects from concept development and experimental design through model development, validation, deployment, publication, and technology transition.
Build and mentor research teams.
Supervise graduate and undergraduate researchers and research staff.
Contribute to instruction, curriculum development, seminars, workshops, and workforce-training activities.
Disseminate research through high-impact publications and technical presentations.
Advance intellectual property and technology transfer.
Support the continued growth, visibility, and research infrastructure of the laboratory and associated academic–government–industry programs.