Job Title Postdoctoral Research Associate Agency Texas A&M University Department Texas A&M Institute of Data Science Proposed Minimum Salary Commensurate Job Location College Station, Texas Job Type Staff Job Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived experiences. Embracing varying opinions and perspectives strengthens our core values which are: Respect, Excellence, Leadership, Loyalty, Integrity, and Selfless Service. Who We Are The Texas A&M Institute of Data Science (TAMIDS) pursues new approaches to data science research, education, operations, and partnerships. These approaches cross college boundaries to connect elements of Data Science from engineering, technology, science and the humanities, and inform wider social challenges. In partnership with over 200 research affiliates from across the Texas A&M University System, work being done by TAMIDS is shaping the future of Data Science research. To learn more, visit https://tamids.tamu.edu/. What We Want The Texas A&M Institute of Data Science (TAMIDS) is excited to announce an opening for a Postdoctoral Research Associate in our cutting-edge Operational Data Science Lab. We are looking for a dynamic individual who is passionate about computer vision and machine learning. In this role, you will develop innovative machine learning solutions, collaborate with interdisciplinary researchers, and apply your 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. We seek someone committed to fostering a cooperative and innovative work environment. If you're ready to make a significant impact and work on exciting projects, we want to hear from you! What You Need To Know Compensation will be commensurate to the selected hire’s experience. A cover letter and resume are strongly recommended. Qualifications Required Education and Experience: + PhD in relevant area. Required Special Knowledge, Skills, and Abilities: + Comprehensive knowledge of foundations, methods and applications of machine learning and deep learning. + Experience with frameworks and libraries for deep learning (e.g., PyTorch). + Experience with models and libraries in computer vision, for image classification (e.g., ResNet), object detection (e.g., YOLO), and segmentation (e.g., Mask-RCNN). + Experience implementing data-intensive workflows for machine learning on high-performance computing platforms. + Ability to work with multidisciplinary teams. + Good communication skills. + Ability to multitask and work cooperatively with others. Preferred Qualifications: + Experience with computer vision including data acquisition and curation, and model development. + Geographic Information Systems (GIS). + Knowledge of applications of computer vision to problems in built environment and/or livestock farming. + Experience in research proposal development. Responsibilities + Research- Independently perform research within the multidisciplinary collaborative groups in Operational Data Science Lab. Research computer vision algorithms and applications in built environment and livestock farming. Produce journal publications, conference papers, and deliver presentations Develop and deliver research-related presentations and short courses. Participate in or lead scientific project development and proposal writing. + Community Engagements- Develop software packages to implement lab research results and provide consultation on their usage. Assist with the organization of community building activities and assists with the day-to-day lab operations. Assist with mentoring research students in the group and/or interdisciplinary student team projects. Why Texas A&M University? We are a prestigious university with strong traditions, Core Values, and a community of caring and collaboration.  Amenities associated with a major university, such as sporting and cultural events, state-of-the-art recreation facilities, the Bush Library and Museum, and much more await you.  Experience all that a big city has to offer but with a reasonable cost-of-living and no long commutes.  + Health (https://www.tamus.edu/business/benefits-administration/medical/) , dental (https://www.tamus.edu/business/benefits-administration/dental/) , vision (https://www.tamus.edu/business/benefits-administration/vision-insurance/) , life and long-term disability insurance (https://www.tamus.edu/business/benefits-administration/life-add/) with Texas A&M contributing to employee health and basic life premiums + 12-15 days (https://employees.tamu.edu/employee-relations/leave/index.html) of annual paid holidays + Up to eight hours of paid sick leave (https://employees.tamu.edu/employee-relations/leave/paid/sick.html)  and at least  eight hours of paid vacation each (https://employees.tamu.edu/employee-relations/leave/paid/vacation.html) month + Automatically enrollment in the Teacher Retirement System of Texas + Health and Wellness: Free exercise programs and release time (https://flourish.tamu.edu/wellness-release-time/) + Professional Development: All employees have access to free  LinkedIn Learning (https://linkedinlearning.tamu.edu/)  training, webinars, and limited financial support to attend conferences, workshops, and more + Employee Tuition Assistance (https://livingwell.tamu.edu/employee-tuition-assistance/) and Educational Release time (https://employees.tamu.edu/employee-relations/leave/paid/educational.html) for completing a degree while a Texas A&M employee Instructions to Applicants: Applications received by Texas A&M University must either have all job application data entered or a resume attached. Failure to provide all job application data or a complete resume could result in an invalid submission and a rejected application. We encourage all applicants to upload a resume or use a LinkedIn profile to pre-populate the online application. All positions are security-sensitive. Applicants are subject to a criminal history investigation, and employment is contingent upon the institution’s verification of credentials and/or other information required by the institution’s procedures, including the completion of the criminal history check. Equal Opportunity/Affirmative Action/Veterans/Disability Employer.