The University of Texas at Austin Research Associate in Austin, Texas

Research Associate

Hiring department

TACC

Monthly salary

OPEN

Hours per week

40.00 Standard from 800AM to 500PM

Posting number

18-05-07-01-0708

Job Status Open

FLSA status Exempt

Earliest Start Date Immediately

Position Duration Funding expected to continue

Position open to all applicants

Location Austin - J. J. Pickle Research Campus (North Austin)

Number of vacancies 1

General Notes

May be filled as Research Scientist based on qualifications.

Required Application Materials

  • A Resume is required in order to apply

  • A Letter of Interest is required in order to apply.

  • A List of 2 References is required in order to apply.

Additional Information

Purpose

The Research Associate position in the Data Management and Statistics (DMS) area at TACC will contribute to research, development, and support activities involving data mining and machine learning technologies and the interfaces by which users can transparently harness these techniques and technologies.

Essential Functions

Responsible for assignments that require the technical knowledge to modify or adapt routine procedures under the direction of a supervisor, to meet special research requirements for data projects hosted at TACC. Working with data providers, consumers, systems experts, and staff to design, develop, deploy, and support scalable high performance machine learning application and systems at TACC. Prepare user documentation and guides to support the usage and operations of data analysis tools and APIs supported and/or developed at TACC. Assists fellow research associates, research scientists, engineers, or faculty members with specific phases of research projects. Explore and understand new techniques and technologies related to support high performance scaleable data analysis. Assist with creating research and system proposals to support work done at TACC and with research partners of TACC. Train and teach the capabilities and potential usages of machine learning techniques in a wide array of research domains and levels of computational abilities. Other related functions as assigned by manager and leadership team.

Marginal/Incidental functions

Other related functions as assigned.

Required qualifications

Ph.D. in Data Science, Computer Science, Statistics, or other related research field with a strong background in machine learning and data analytics. Experience implementing and supporting a machine learning and data analytics applications or workflows. Good programing skill with either Java or Python progamming language. The ability to learn, adapt, and teach new technologies to enable new capabilities or improve on existing ones. Experience collaborating with a team of domain and technology experts implementing solutions based on machine learning and natural language processing techniques. Excellent written and verbal communications skills. Equivalent combination of relevant education and experience may be substituted as appropriate.

Preferred Qualifications

One or more of the following qualifications are strongly desired but not required to apply. Two or more years experience in developing and implementing machine learning algorithm applications in an academic research environment. Two or more years working experiences with high performance computing resources and data centers. Practical experiences with teaching, deploy and using at least one of common deep learning frameworks such as Caffe, Tensorflow, deeplearning4j, Torch. Experience developing applications in large parallel environments using tools such as Hadoop, Hbase and SparkML. Excellent problem solving and strategic thinking skills. Familiar with stadarnd parallel computing tools and interface, such as MPI. Recent peer-reviewed publications in computer science fields relevant to machine learning, big data analysis or high performance computing.

Working conditions

May work around standard office conditions

May work around electrical and mechanical hazards

Repetitive use of a keyboard at a workstation

A criminal history background check will be required for finalist(s) under consideration for this position.

The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. This position has the option to elect the Optional Retirement Program (ORP) instead of TRS, subject to the position being 40 hours per week and at least 135 days in length.

The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.

If hired, you will be required to complete the federal Employment Eligibility Verification form, I-9. You will be required to present acceptable, original documents to prove your identity and authorization to work in the United States. Information from the documents will be submitted to the federal E-Verify system for verification. Documents must be presented no later than the third day of employment. Failure to do so will result in dismissal.

UT Austin is a Tobacco-free Campus