Post-Doctoral Fellow in Acoustics AF7771

Oklahoma State University; Stillwater (OK); On-site; USD 55,000 - 75,000; Full time

Job summary

Oklahoma State University’s School of Mechanical and Aerospace Engineering invites applications for a Post-Doctoral Fellow position in Acoustics. The successful candidate will lead interdisciplinary research at the intersection of machine learning, physical and computational acoustics, vibration/noise control, and signal processing.

The role emphasizes independent research, AI-acoustics method development, project management, and mentoring graduate and undergraduate students, with collaboration

Qualifications

• Ph.D. in Mechanical or Aerospace Engineering or related field.
• Strong background in acoustics, vibration/NVH, audio/speech processing.
• Demonstrated expertise in ML/AI methods (deep learning, physics-informed learning, surrogate modeling).

Responsibilities

• Develop ML, DL, and physics-aware models for acoustics, NVH, audio/speech, and signal processing.
• Build surrogate models and data-driven optimization for vibroacoustic systems.
• Design experiments to validate methodologies and build demos.
• Prepare peer-reviewed publications and disseminate research.
• Develop reproducible code and documentation for dissemination.

Skills

Machine learning

Acoustics

Python

PyTorch / TensorFlow

Signal processing

Research leadership

Education

Ph.D. in Mechanical/Aerospace Engineering or related field

Tools

Python

MATLAB

COMSOL

FEM/CFD

Job description

Post-Doctoral Fellow - Acoustics

Position Summary:

The School of Mechanical and Aerospace Engineering at Oklahoma State University invites applications for a Post-Doctoral Fellow position to join Prof.Yangfan Liu’s research group. The successful candidate will lead interdisciplinary research at the intersection of machine learning, physical and computational acoustics, vibration/noise control, and signal processing.

This is a postdoctoral appointment intended for candidates seeking to contribute and manage ongoing sponsored research projects and supervise students. Ideal candidates will have a strong cross-disciplinary background in acoustics, audio/speech or acoustic signal processing, computational acoustics, and modern machine learning. Key responsibilities include conducting independent research, developing AI-acoustics methodologies with strong practical and translational value, managing projects, contributing to proposals and sponsor reports, preparing high-quality peer-reviewed publications, and mentoring graduate and undergraduate students. The position offers opportunities to collaborate with academic researchers, industrial partners, and students across multiple disciplines.

Responsibilities and Duties

50% – Research

• Develop machine learning, deep learning, and physics-aware models for acoustics, vibration, NVH, audio/speech, and signal-processing applications.
• Build surrogate models, inverse-design frameworks, and data-driven optimization methods for acoustic materials, computational acoustics, compressor/vehicle-cabin acoustics, or related vibroacoustic systems.
• Design and perform experiments to validate developed methodologies and build proof-of-concept demos.
• Prepare peer-reviewed publications in leading journals and conferences in acoustics, signal processing, machine learning, mechanical engineering, and related fields.
• Develop reproducible code, analysis pipelines, and technical documentation to support research dissemination and technology transfer.

20% – Research Management

• Manage day-to-day project tasks to meet sponsor requirements, research milestones, and publication timelines.
• Coordinate research activities among faculty, students, and external collaborators; organize technical meetings and track deliverables.
• Provide technical leadership on model development, data analysis, simulation/measurement workflows, and manuscript preparation.

20% – Proposal Development & Professional Service

• Contribute to research proposals for federal agencies, industry sponsors, and university-industry collaborative programs.
• Assist with grant management, sponsor communications, technical reporting, and partnership development.
• Represent the research group at conferences, workshops, sponsor meetings, and professional events.
• Participate in peer review, professional societies, and academic service activities as appropriate.

10% – Student Mentoring

• Mentor graduate and undergraduate students in machine learning, acoustics, signal processing, simulation, and data analysis.
• Guide students in research planning, coding practices, experiment/simulation design, data interpretation, technical writing, and presentations.

Qualifications:

• Ph.D.in Mechanical or Aerospace Engineering, Acoustics, Electrical and Computer Engineering, Computer Science, Applied Physics, or a closely related field.
• Strong background in acoustics, vibration/NVH, audio/speech processing, acoustic signal processing, computational acoustics, or related areas.
• Demonstrated expertise in machine learning or AI methods, such as deep learning, physics-informed or physics-aware learning, surrogate modeling, inverse design, generative models, optimization, or uncertainty-aware modeling.
• Strong record of scholarly research, including first-author or major-contribution publications in high-quality peer-reviewed journals and conferences.
• Experience with numerical simulation, experimental/measurement data, acoustic materials/structures, vehicle-cabin acoustics, HAV equipment noise, aerodynamic noise, or speech/audio systems is preferred.
• Proficiency in research programming and data analysis, preferably using Python and ML frameworks such as PyTorch or TensorFlow; experience with MATLAB, COMSOL, FEM/CFD/acoustic tools, or signal-processing toolchains is a plus.
• Demonstrated ability to communicate complex technical concepts clearly in reports, manuscripts, presentations, and interdisciplinary team settings.
• Experience mentoring students, coordinating research tasks, leading collaborative projects, or managing team deliverables is strongly preferred.

SALARY AND BENEFITS:

Salary will be commensurate with education, experience, qualifications, appointment percentage, and contingent on available funding. Benefits, if applicable, will follow Oklahoma State University policies for part-time postdoctoral appointments. Applicants should refer to Oklahoma State University Human Resources for current benefits information.

Questions about the position should be directed to Prof.Yangfan Liu at [e-mail].