Instructional Assistant Professor and Knowledge Development Fellow (TAMIDS)

Academic Professional Track Faculty (Non-Tenure)

The Department of Statistics (STAT) in the College of Arts & Sciences at Texas A&M University seeks one Academic Professional Track (APT) faculty position for the appointment of Instructional Assistant Professor, which will begin on August 1, 2025. This position also includes an administrative appointment as a Knowledge Development Fellow with the Texas A&M Institute of Data Science (TAMIDS). This is a non-tenure accruing, full-time, 9-month appointment. Duties and responsibilities for this position will be split 50/50 between STAT and TAMIDS.

Statistics duties will include teaching 3 courses per academic year for both undergraduate and M.S. level courses as well as committee service that will complement or balance teaching duties and/or curriculum development. Duties for TAMIDS will include an administrative appointment as Knowledge Development Fellow, with an initial term of three years. The Knowledge Development Fellow will conduct training, consultancy, and educational research activities in Data Science under the direction of the TAMIDS Director within the TAMIDS Knowledge Development Laboratory u.tamu.edu/Knowledge-Lab. They will be responsible for delivering and developing short courses in Data Science for workforce and skills development; organizing and mentoring within TAMIDS student training and engagement programs; conducting consultancy and mentoring student consultants, as well as collaboratively developing research proposals related to and arising from these activities. This jointly supported position will help broaden collaboration between STAT and TAMIDS, and strengthen the STAT role in the ecosystem for Data Science and AI at Texas A&M.

Successful applicants must have a doctorate in Statistics, Data Science, or related field and previous experience in teaching at the undergraduate level is required. Interested applicants should send a cover letter, current CV, contact information for three (3) references, and a personal statement to include philosophy and plans for research, teaching and service, as applicable. To apply, please visit apply.interfolio.com/156662. Review of applicants will begin immediately. For questions, email inquiries to Dr. Alan Dabney, Search Committee Chair, at hiring@stat.tamu.edu.

Research Specialist I

TAMIDS is seeking a Research Specialist I who will develop data analytics functionality and software systems that support research collaborations and operation of TAMIDS programs. The holder of this position will also join TAMIDS service role in providing consultation to Texas A&M faculty, researchers, and students to assist them in integrating Data Science tools and methods into their research and educational programs.

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Postdoctoral Researcher (Computer Vision)

Postdoctoral Research Associate R-079986

TAMIDS is seeking a Postdoctoral Research Associate for the Operational Data Science Lab who will develop innovative machine learning solutions, collaborate with interdisciplinary researchers, and apply their expertise to impactful projects in the built environment and livestock farming. The ideal candidate will have strong programming skills in computer vision and artificial intelligence, a collaborative spirit, and a team-oriented mindset.

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None currently

Urban AI Student Workers

The TAMIDS Urban AI Lab is looking to hire 1-2 Mobile React Native Developers to join their team. This is a great opportunity to gain experience in mobile app development and work closely with our team on many exciting projects. This part-time position requires:

• 1–2 years of experience developing cross-platform mobile applications using React Native with a strong understanding of its libraries and frameworks.
• Proficiency in TypeScript and NPM in mobile app development.
• Hands-on experience with 2D image processing and its integration into applications.
• Knowledge of AR frameworks compatible with React Native, such as ViroReact.
• Experience with RESTful APIs.
• Experience writing tests to ensure code reliability and maintainability.
• Experience using Git and GitHub for version control and collaborative development.
• Ability to work with designers to implement responsive and visually appealing UI/UX.
• Proven ability to work independently and meet deadlines in a fast-paced environment.

Those who are interested should email their resume and a brief description of their relevant experience to Dr. Xinyue Ye at xinyue.ye@tamu.edu.

Student Technician: Finite Element Modeling

Position Type: Part-Time Student Employment

Description: The Digital Twin Lab at the Texas A&M Institute of Data Science is seeking a graduate student to contribute to a project focused on reduced order modeling. This role is ideal for individuals with a strong foundation in computational sciences, specifically those proficient in the Finite Element Method (FEM).

Qualifications:

1. Background in computational sciences, with a focus on the Finite Element Method.
2. Experience in programming with C++ and high-performance computing (HPC).
3. Familiarity with open-source FEM packages such as MFEM, Deal.II, or FEniCs.
4. Experience with meshing software, notably GMSH.
5. Extensive experience in utilizing commercial software platforms like ANSYS or Abaqus is strongly encouraged

Apply through our online form by clicking the link below:

For more details please contact Suprano Bhattacharyya at suparnob@tamu.edu.

Student Assistant: Operational Data Science Lab

Position Type: Part-Time Student Employment

Description: The TAMIDS Operational Data Science Lab is seeking a Student Assistant to join our team for computer vision research projects. The projects extensively use Texas A&M High Performance Research Computing (HPRC) systems for data processing. This position offers an excellent opportunity to gain hands-on experience in computer vision, data science, and HPC. Contributors will also participate in scientific publications and communications in journals and conferences.

Key Responsibilities:

• Set up hardware for data acquisition, storage, and management.
• Research and analyze the latest advancements in computer vision and natural language processing.
• Develop algorithms, curate datasets, and conduct experiments.
• Document methodologies, algorithms, and findings for future reference and potential publication.

What we need:

• Strong programming skills in Python, with experience in computer vision libraries (e.g., OpenCV) and deep learning frameworks (e.g., PyTorch).
• Experience with large-scale video data acquisition, storage, and management, including preparing training datasets from raw video footage (e.g., frame sampling, annotation) and designing experiments.
• Familiarity with social media data acquisition and analysis, particularly from platforms like Twitter/X.
• Ability to navigate, debug, and run complex code on multiple platforms (Windows and Linux).
• Solid understanding of computer vision techniques, including but not limited to image classification, object detection, instance segmentation, keypoint detection, and pose estimation.
• Experience with natural language processing (NLP), including text processing and designing natural language classification experiments.

Outcomes:

• Gain hands-on experience in end-to-end project development, including camera setup, data collection, annotation, model design, training, and inference.
• Work on challenging and cutting-edge machine learning solutions in computer vision and natural language processing.
• Collaborate with highly skilled professionals across multiple domains and gain domain-specific expertise.
• Opportunities to present and publish your work at conferences and in research journals.

Apply through our online form by clicking the link below:

For more details, please contact Dr. Yalong Pi at piyalong@tamu.edu.