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Parttime Data Science Jobs in Oklahoma (NOW HIRING)

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Parttime Data Science information

What is the difference between Parttime Data Science vs Parttime Data Analyst?

AspectParttime Data ScienceParttime Data Analyst
Required SkillsStatistical analysis, programming (Python/R), machine learningData visualization, basic statistics, Excel, SQL
Work EnvironmentTech companies, startups, research projectsBusiness, marketing, finance departments
Common CertificationsCertified Data Scientist, Python certificationsMicrosoft Excel, SQL certifications

Parttime Data Science roles typically require advanced skills in programming and machine learning, often found in tech or research settings. In contrast, Parttime Data Analyst positions focus on data visualization and basic analysis, suitable for business or marketing environments. Both roles are popular in various industries, but Data Science generally demands more technical credentials and programming expertise.

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Infographic showing various Parttime Data Science job openings in Oklahoma as of August 2026, with employment types broken down into 100% Part Time. Highlights an 65% In-person, and 35% Remote job distribution.

Post-Doctoral Fellow in Acoustics AF7772

The OSU/A&M System

Stillwater, OK โ€ข On-site

$46K - $62K/yr

Full-time, Part-time

Posted 6 days ago


Job description

Post-Doctoral Fellow - Acoustics

Position Summary:

The School of Mechanical and Aerospace Engineering at Oklahoma State University invites applications for a part-time 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.

SPECIAL INSTRUCTIONS TO APPLICANTS:

The process of reviewing applications will begin soon and will continue until a successful candidate is selected.

Interested and qualified candidates should submit a single PDF file including:

  • a cover letter addressing research interests, relevant experience, and skills that fulfill the requirements;
  • a Curriculum Vitae;
  • up to three representative publications.

Questions about the position should be directed to Prof. Yangfan Liu at yangfan.liu@okstate.edu.