Research Associate - R and D Natural Language Processing Expert at The University of Texas at Austin
Austin, Texas, United States
🇺🇸 (Posted Jun 18 2018)
About the company
The University of Texas at Austin is one of the largest public universities in the United States. Founded in 1883, the university has grown from a single building, eight teachers, two departments and 221 students to a 350-acre main campus with 21,000 faculty and staff, 16 colleges and schools and more than 50,000 students.
Research, development and evaluation of content, understanding algorithms with focus on decision support for extracting, resolving and inferencing over data derived from text-based content.
Design, develop and evaluate algorithms and software in support of sponsored research projects. Contribute to research publications, evaluation reports and software documentation. Perform knowledge acquisition and documentation of project requirements and subject-specific expertise. Provide technical and research leadership. Prepare and deliver presentations of project updates and communicate effectively with team members and supervisors for timely implementation of project requirements.
Skills & requirements
PhD in computer/software engineering, information/computer science, or other applied sciences. Demonstrated experience with a variety of natural language processing and computational linguistics techniques. US Citizen: Applicant selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information at the level appropriate to the project requirements of the position. Evidence of skills in the following areas: working with new technologies, being highly organized, planning and coordinating multiple tasks, effective time management, attention to detail, effective problem solving skills, using excellent judgment, working independently with sensitive and confidential information, maintaining a professional demeanor, working as a team member without daily supervision, effectively communicating with diverse groups of clients, working under pressure, accepting supervision and demonstrating regular/punctual attendance.
Significant experience with unstructured text processing, natural language processing, and computational linguistics (entity extraction, entity disambiguation, co-reference resolution, language generation, topic modeling, etc.) Demonstrated, in-depth knowledge of the strengths and weaknesses of various machine learning algorithms. Familiarity with probabilistic latent variable models, such as Latent Dirichlet Allocation, and sampling-based approximation methods. Experience with a variety of application domains and datasets for machine learning problems. Strong software programming skills (Java, Python, variety of scripting languages). Familiarity with software version control systems and formal software engineering processes. Familiarity with formal knowledge model representations (ontologies). Familiarity with graph-based reasoning and scalable architectures. Eligibility for immediate access to classified information. Cumulative GPA of at least 3.0.
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