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Online Machine Learning Postdoc Jobs in Bryan, TX

TAMU Athletics - 878 Houston Street, College Station, TX 77843 Note: online applications accepted ... Our careers are filled with purpose and encourage learning, growth, and meaningful impact. Apply ...

Address : 1248 TAMU, College Station, TX 77843 Note: online applications accepted only. * Schedule ... Our careers are filled with purpose and encourage learning, growth, and meaningful impact. Apply ...

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Online Machine Learning Postdoc information

See Bryan, TX salary details

$21.7K

$47.9K

$63.2K

How much do online machine learning postdoc jobs pay per year?

As of Sep 7, 2026, the average yearly pay for online machine learning postdoc in Bryan, TX is $47,914.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,400.00 and $55,300.00 per year, depending on experience, location, and employer.

What is the difference between Online Machine Learning Postdoc vs Data Scientist?

AspectOnline Machine Learning PostdocData Scientist
Required CredentialsPhD in Computer Science, Machine Learning, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; often a PhD is preferred but not required
Work EnvironmentAcademic research settings, universities, research labsIndustry companies, tech firms, startups, corporate analytics teams
Employer & Industry UsagePrimarily academic, research-focused roles in universities or research institutionsCommercial sector, product development, data analysis, and business intelligence

The Online Machine Learning Postdoc typically focuses on academic research, exploring new algorithms and theories in machine learning, often in a university setting. In contrast, a Data Scientist applies machine learning techniques to solve real-world business problems in industry. While both roles require strong technical skills, the Postdoc emphasizes research and publication, whereas Data Scientists focus on data analysis and product development.

What are the most commonly searched types of Machine Learning Postdoc jobs in Bryan, TX?

The most popular types of Machine Learning Postdoc jobs in Bryan, TX are:

What cities near Bryan, TX are hiring for Online Machine Learning Postdoc jobs?

Cities near Bryan, TX with the most Online Machine Learning Postdoc job openings:

Tenure-Track/Tenured: Assistant or Associate Professor, AI for Autonomous Agricultural Systems-Robot

Texas A&M University

College Station, TX • On-site

Full-time

Re-posted 4 days ago


Key responsibilities

  • Develop an integrated research and teaching program focused on advancing intelligent agricultural machinery systems.

  • Lead innovation in the development and in-field evaluation of AI-enabled autonomous agricultural systems to improve efficiency, reduce resource use, and increase resilience.

  • Develop and teach courses related to agricultural autonomy, robotics, and AI-enabled systems for undergraduate and graduate students.


Texas A&M University rating

7.8

Company rating: 7.8 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

237th of 631 rated colleges and universities


Job description

Description
Position Description: The Department of Biological and Agricultural Engineering in the College of Agriculture and Life Sciences at Texas A&M University invites applications for a 9-month, full time position in Artificial IntelIigence (AI) for Autonomous Agricultural Systems- Robotics & Sensing. Applicants will be considered for the titles of Assistant Professor (Tenure-Track) and Associate Professor (Tenured). The department has top-ranked graduate and undergraduate programs and a strong research emphasis in machinery systems and postharvest process engineering. This position is part of a four-position cluster hire in AI in Agriculture across the College of Agriculture and Life Sciences to build research capacity in this area.
Within this cluster, the Biological and Agricultural Engineering position focuses on AI-enabled autonomy, robotics, and precision operations in agricultural production. This position should address major challenges facing agriculture, such as efficiency, labor costs and availability, emerging biotic threats, water use and efficiency, and soil health. This position requires strong technical expertise in AI, sensing, automation and controls, or robotics, as well as knowledge of agricultural systems.
Duties and Responsibilities: The successful candidate will develop an internationally recognized integrated research and teaching program that advances intelligent agricultural machinery systems and prepares students for careers at the intersection of agriculture and technology. Potential research areas may include, but are not limited to agricultural autonomy, collaborative robotics, AI-enabled sensing systems, cyber-physical systems for agriculture, federated learning, edge computing, development of novel AI algorithms for agricultural applications, embodied AI, simulation to reality transfer, and systems engineering incorporating big data and artificial intelligence.
Agriculture will be transformed in the coming decades by the adoption of robotics and data-driven systems. This position will lead innovation in development and in-field evaluation of these agricultural systems to increase farmer profitability, minimize resource use, and enhance the resilience of agriculture in Texas and beyond. While the candidate should have strong engineering expertise, transdisciplinary collaboration will be necessary for success in this role. Multiple resources are available through the college and university to support collaborative efforts. These include, but are not limited to, the Texas A&M Institute of Data Science and the High Performance Research Computing Center, which recently brought online the most powerful university supercomputer in the US. AgriLife has invested in data-driven agriculture initiatives such as the Automated Precision Phenotyping Greenhouse and the AgriTech Innovation Farm Hub. Furthermore, AgriLife has 13 research and extension centers across Texas and maintains strong connections with commodity groups and farmer organizations.
The successful applicant will develop and teach courses in the Department of Biological and Agricultural Engineering. The individual will develop courses in agricultural autonomy/robotics for undergraduate and graduate students in Biological and Agricultural Engineering and Agricultural Systems Management. An undergraduate minor in AI-Enabled Agricultural Systems will be established with courses developed from this cluster hire.
The individual will advise and mentor undergraduate and graduate students and other research personnel. The successful candidate will attract extramural funding and publish research in appropriate peer-reviewed journals. They will participate in service activities, both internally and professionally, to complement their teaching and research programs.
Qualifications
Required Qualifications: Applicants must possess a Ph.D. in Biological and Agricultural Engineering or a closely related engineering discipline. Candidates who have completed all Ph.D. requirements except the dissertation (ABD) will be considered provided they demonstrate clear progress toward completion. Candidates must have demonstrated experience or potential to build strong research and teaching programs. Successful candidates are expected to have effective verbal and written skills, an ability to work both independently and in multi-disciplinary teams, and a willingness to advise and mentor students.
Desired Qualifications: Applicants should be licensed or qualified to obtain a license as a Professional Engineer. Experience deploying automated systems in agricultural environments is highly desirable.
Application Instructions
Application Instructions: Interested applicants must apply through the Texas A&M University faculty job board hosted by Interfolio (apply.interfolio.com/189784 )and upload the following: 1) cover letter; 2) curriculum vitae; 3) a 3-page maximum research, teaching and service statement that includes your vision for a research program at Texas A&M and your teaching philosophy, methods, and potential courses. Clearly indicate your vison for how AI will impact the practice of science and teaching and learning; and 4) names and contact information of three (3) professional references. Clearly indicate in the research and teaching statements your vision for how AI will impact the practice of science and teaching and learning. Review of applications will begin on September 30, 2026.
Please direct any questions to Dr. Bobby Hardin at robert.hardin@ag.tamu.edu.
Equal Employment Opportunity Statement
Equal Opportunity/Veterans/Disability Employer.

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