The Texas A&M Institute of Data Science (TAMIDS: https://tamids.tamu.edu) and the newly established NSF-funded Research Institute on the Foundations of Interdisciplinary Data Science at Texas A&M University (FIDS: http://FIDS.tamu.edu) are seeking to recruit a postdoctoral research associate to work in the area of machine learning, statistical and computational methods for the modeling and analysis of high-dimensional and graph-based data. Candidates should possess a Ph.D. in Data Science, Electrical Engineering, Computer Science, Statistics, Mathematics, or a related area.
The postdoc will join a group led by Nick Duffield, Dileep Kalathil, Krishna Narayanan and Xiaoning Qian with methodological interests that span graph data streaming, graph embedding and learning, graph signal processing and reinforcement learning, with applications that include intelligent transportation, information systems and computer networking. We seek a candidate who is able to synthesize novel research problems that integrate across two or more of these areas. Candidates are expected to have strong programming skills, including use of R/Python/Matlab.
The position is designed as a career-building step for a junior scholar, with the development of a research program as its primary focus. The postdoc will have opportunities to work on cutting edge problems with researchers from various related disciplines affiliated with TAMIDS and FIDS. The postdoc will also engage with the broader mission of TAMIDS for one day per week on average. Examples of such engagements include mentoring graduate student Data Science team projects, creating and teaching a short course related to their research, or collaborating or consulting with other researchers in affiliated areas of Data Science.
How To Apply
Further specifics concerning the position and application procedures can be found on the Texas A&M Jobs Worksite
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