Texas A&M University, Texas A&M Institute of Data Science

Position ID:Texas A&M University-Texas A&M Institute of Data Science-REIII1 [#21350, R-047418]
Position Title: Research Engineer in Data Science for Radio Infrastructure
Position Type:Other
Position Location:College Station, Texas 77845, United States [map]
Subject Area: Data Science / Machine Learning
Appl Deadline:none
Position Description:    

The TEES Research Engineer III will work with operational data arising from infrastructure and the built environment to derive analyses and tools that will enhance design, management, operations, and user experience. The TEES Research Engineer III will work in part on project funded by the National Institute of Standards and Technology (NIST) to develop analysis, tools, and information systems that will use geospatial environmental and facilities data and usage event streams to inform capacity planning of radio system infrastructure for emergency management. The project is a collaboration between the Texas A&M Departments of Electrical & Computer Engineer and of Visualization, the Texas A&M Institute of Data Science (TAMIDS) and Texas A&M Internet2 Technology Evaluation Center (ITEC). The TEES Research Engineer III will also work on projects more broadly related to infrastructure, urban science, and Data Science, write research article and reports, mentor student participation, and develop proposals for further research funding. The position should appeal to someone with a broad set of systems, computing, and Data Science skills who enjoys harnessing state-of-the-art analytic methods to have practical and beneficial impact on infrastructure systems and collaborating with practitioners to help realize their results. 

The advent of advanced sensors and instrumentation deployed in the facilities and systems of public infrastructure is yielding immense amounts of operational data. This provides compelling opportunities for Data Scientists to partner with operators to enhance many aspects of the infrastructure, including design, management, safety, and user experience. Our cross-disciplinary team, drawn from Texas A&M’s Department of Electrical & Computer Engineering and the Operational Data Science Lab at the Texas A&M Institute of Data Science, seeks to integrate across foundations and practice by (i) applying methods from Data Science, Machine Learning and AI to model and understand the complex relationships within high-dimensional operational datasets including geospatial data and event streams; (ii) developing algorithms that optimize design and operations of facilities subject to outcome goals including cost and performance; (iii) embodying our results in accessible information systems and web-based interfaces; and (iv) working with operational partners for data acquisition, determining relevant project goals and analyses, and aiding implementation.

Responsibilities: 
  • Develop and apply advanced data analytics methods to model usage and performance in radio infrastructure and broadly in urban data science. 
  • Develop information systems to integrate and house data from multiple sources. 
  • Build tools for data retrieval, reporting and visualization, and scenario exploration though Digital Twin incorporating data driven models. 
  • Mentor and support student participation. 
  • Work with external project partners to acquire data and knowledge of problem context. 
  • Work with interdisciplinary project team to specify system function and overall design. 
  • Develop timeline for system development, including milestones for evaluation and testing. 
  • Write research articles and project reports. 
  • Document system design, functions, and usage; develop and deliver training for users. 
  • Collaborate on preparation of proposals for further funding. 
  • Perform other duties as assigned. 

Required Education: Bachelor’s degree in Engineering, Science or related field or equivalent combination of education and experience. 

Required Experience: Four years of related experience. 

Preferred Education: Appropriate doctoral degree 

Preferred Experience
  • Experience with applications of Data Science for infrastructure and the built environment, with experience related to radio infrastructure a plus 
  • Experience working with data throughout its lifecycle: acquisition, storage and management, computation and analytics, query and reporting functions, interfaces and presentation
  • Experience developing software and systems for large-scale data analytics in science, engineering, or business 

Knowledge, Skills and Abilities: 
  • Proficiency with common programming languages such as C, C++ and Python
  • Knowledge of common Data Science libraries in Python 
  • Knowledge of AI/ML frameworks such as TensorFlow, PyTorch, and Keras 
  • Knowledge of GIS and geospatial data systems 
  • Knowledge of data management and databases 
  • Knowledge of radio communications technologies and standards, such as LTE and 5G 
  • Knowledge of high-performance computational and cloud-based systems, tools and architectures 
  • Knowledge of methods for real-world data wrangling and cleaning 
  • Familiarity with design of web-based dashboards and user-interfaces 
  • Ability to cultivate and maintain professional working relationships with people of diverse backgrounds 
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 committed to diversity.

We are not accepting applications for this job through AcademicJobsOnline.Org right now. Please apply at https://tamus.wd1.myworkdayjobs.com/TEES_External/job/College-Station-TEES/Research-Engineer-III_R-047418.
Contact: Jennifer South, 979-458-6252
Email: email
Postal Mail:
Texas A&M Institute of Data Science (TAMIDS)
155 Ireland Street
John R. Blocker Bldg, Suite 227
College Station, TX.77845-3156
Web Page: tamids.tamu.edu