Research Associate for Artificial Intelligence and Machine Learning
Company: University of Texas at Austin
Location: Austin
Posted on: September 3, 2024
Job Description:
Job Posting Title:Research Associate for Artificial Intelligence
and Machine Learning----Hiring Department:Texas Advanced Computing
Center----Position Open To:All Applicants----Weekly Scheduled
Hours:40----FLSA Status:Exempt----Earliest Start
Date:Immediately----Position Duration:Expected to
Continue----Location:PICKLE RESEARCH CAMPUS----Job Details:General
Notes The Texas Advanced Computing Center (TACC) at The University
of Texas at Austin is one of the leading supercomputing centers in
the world, supporting advances in computational research by
thousands of researchers and students. TACC staff help researchers
and educators use advanced computing, visualization, and storage
technologies effectively, and conduct research and development to
make these technologies more powerful, more reliable, and easier to
use. TACC staff also educate and train the next generation of
researchers, empowering them to make discoveries that advance
knowledge and change the world.If you are not sure that you're 100%
qualified, but up for the challenge - we want you to apply. We
believe skills are transferable and passion for our mission goes a
long way. fosters a culture of innovation, passion, and fun by
encouraging staff members to actively collaborate to investigate
the latest technologies, team up for charities, and celebrate
successes together. TACC promotes a healthy workplace by helping
employees achieve balance between their personal and professional
lives to increase employee engagement, job satisfaction, and
overall well-being.Candidates will need to upload a resume, letter
of interest, and the names of three references to apply for this
position.UT Austin offers a competitive benefits package that
includes:
- 100% employer-paid basic medical coverage
- Retirement contributions
- Paid vacation and sick time
- Paid holidaysPlease visit our websiteto learn more about the
total offered.PurposeThe Research Associate will work in the
Scalable Computational Intelligence group as they support
researchers leveraging modern AI/ML techniques. The ideal candidate
will have a strong background in data analytics and a passion for
research across many science and engineering
domains.Responsibilities
- Consult and work with data providers, analysts, systems
experts, and other research staff to design, develop, and deploy
machine learning and data analytics systems supporting defined
project requirements.
- Mentor TACC staff in machine learning and data analysis
techniques and technologies and the support needed for them to work
within an HPC cluster environment.
- Support the application of AI/ML techniques across various set
of topics and domains.
- Support training of AI/ML techniques and best practices to a
broad range of researchers
- Collaborate and propose new funding opportunities supporting
research done at TACC.
- Prepare reviewed papers, technical reports, design, and
requirements of data analytic techniques and systems,
optimizations, and novel applications across domains supported at
TACC.
- Stay at the forefront of new techniques and technologies
applicable to AI/ML systems that support implementations in various
science and engineering domains.
- Other related functions as assigned.Required Qualifications
- Ph. D. in science, engineering, or other related research
fields with a strong background in applied data analytics
techniques for research.
- Experience working with AI/ML platforms and algorithms.
- Experience working with domain experts, researchers, and
stakeholders to support different applications for their data
analytics needs.
- The ability to learn and adapt new technologies to enable new
capabilities or improve existing ones.
- Excellent written and verbal communication skills.Relevant
education and experience may be substituted as
appropriate.Preferred Qualifications
- Experience in analyzing both measured and simulated data
sources for scientific and engineering research.
- Experience supporting and extending open-source and open-data
products for different research communities.
- Familiarity with data analysis systems and workflows.
- Experience training and mentoring researchers in best practices
when creating data workflows.
- Strong problem-solving and strategic thinking skills.Salary
Range$90,000 + depending on qualificationsWorking Conditions
- Typical Office Environment
- Repetitive use of a keyboardRequired Materials
- Resume/CV
- 3 work references with their contact information; at least one
reference should be from a supervisor
- Letter of interestImportant for applicants who are NOT current
university employees or contingent workers: You will be prompted to
submit your resume in the first step of the online job application
process. Then, any additional Required Materials will be uploaded
in the My Experience section; you can multi-select the additional
files or click the Upload button for each file. Before submitting
your online job application, ensure thatALLRequired Materials have
been uploaded. Once your job application has been submitted, you
cannot make changes.Important for Current university employees and
contingent workers: As a current university employee or contingent
worker, you MUST apply within Workday by searching for Find Jobs.
Before you apply though, log-in to Workday, navigate to your Worker
Profile, click the Career link in the left-hand navigation menu and
then update the sections in your Professional Profile. This
information will be pulled in to your application. The application
is one page and you will need to click the Upload button multiple
times in order to attach your Resume, References and any additional
Required Materials noted above.----Employment Eligibility:Regular
staff who have been employed in their current position for the last
six continuous months are eligible for openings being recruited for
through University-Wide or Open Recruiting, to include both
promotional opportunities and lateral transfers. Staff who are
promotion/transfer eligible may apply for positions without
supervisor approval.----Retirement Plan Eligibility: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.----Background Checks:A criminal history background check
will be required for finalist(s) under consideration for this
position.----Equal Opportunity Employer:The University of Texas at
Austin, as an ,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.----Pay Transparency:The University of Texas at Austin
will not discharge or in any other manner discriminate against
employees or applicants because they have inquired about,
discussed, or disclosed their own pay or the pay of another
employee or applicant. However, employees who have access to the
compensation information of other employees or applicants as a part
of their essential job functions cannot disclose the pay of other
employees or applicants to individuals who do not otherwise have
access to compensation information, unless the disclosure is (a) in
response to a formal complaint or charge, (b) in furtherance of an
investigation, proceeding, hearing, or action, including an
investigation conducted by the employer, or (c) consistent with the
contractor's legal duty to furnish information.----Employment
Eligibility Verification:If hired, you will be required to complete
the federal Employment Eligibility Verification I-9 form. You will
be required to present acceptable and original to prove your
identity and authorization to work in the United States. Documents
need to be presented no later than the third day of employment.
Failure to do so will result in loss of employment at the
university.----E-Verify:The University of Texas at Austin use
E-Verify to check the work authorization of all new hires effective
May 2015. The university's company ID number for purposes of
E-Verify is 854197. For more information about E-Verify, please see
the following:
- [PDF]
- [PDF]
- [PDF]
- [PDF]----Compliance:Employees may be required to report
violations of law under Title IX and the Jeanne Clery Disclosure of
Campus Security Policy and Crime Statistics Act (Clery Act). If
this position is identified a Campus Security Authority (Clery
Act), you will be notified and provided resources for reporting.
Responsible employees under Title IX are defined and outlined in
.The Clery Act requires all prospective employees be notified of
the availability of the Annual Security and Fire Safety report. You
may or obtain a copy at University Compliance Services, 1616
Guadalupe Street, UTA 2.206, Austin, Texas 78701.
Keywords: University of Texas at Austin, Austin , Research Associate for Artificial Intelligence and Machine Learning, Other , Austin, Texas
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