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Multimodal Learning Jobs in Leander, TX (NOW HIRING)

... active, multimodal, and sustainable transportation. If you are looking to join an innovative ... learning. Required This position requires a combination of skills, experience and education ...

Material Handler 2

Austin, TX · On-site

$16.50 - $20/hr

... multimodal transportation terminal, intermodal yard, warehouse, or dock environment, directly ... Perform tasks under appropriate supervision while learning equipment operation, safety protocols ...

TDM Program Manager

Austin, TX · On-site

$80K - $100K/yr

... active, multimodal, and sustainable transportation. If you are looking to join an innovative ... engaging in continuous learning and integrating this knowledge into projects, including an ...

... generation, multimodal inference, and long‑context workloads. * Instrument and analyze ... Experience applying machine learning techniques to systems optimization or performance analysis.

Whether supporting highways, bridges, transit and rail, or multimodal infrastructure, our team ... Foster a culture of employee engagement, collaboration, innovation, learning, and positive employee ...

Showing results 41-60

Multimodal Learning information

See Leander, TX salary details

$20.1K

$58.9K

$109.4K

How much do multimodal learning jobs pay per year?

As of Aug 22, 2026, the average yearly pay for multimodal learning in Leander, TX is $58,947.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,200.00 and $68,800.00 per year, depending on experience, location, and employer.

What is multimodal learning?

Multimodal learning is an area of machine learning that involves integrating and processing information from multiple types of data, such as text, images, audio, and video. The goal is to create models that can understand and make predictions based on more than one data modality, similar to how humans use various senses. This approach is used in applications like speech recognition with visual cues, image captioning, and video analysis. By combining different data types, multimodal learning systems can achieve better accuracy and more robust understanding.

What are the key skills and qualifications needed to thrive in multimodal learning, and why are they important?

To excel as a Multimodal Learning Specialist, you need a solid background in machine learning, data science, and computer vision, often supported by an advanced degree in a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, experience integrating data from diverse sources (e.g., text, audio, images), and knowledge of relevant algorithms are crucial. Strong problem-solving abilities, creativity, and effective collaboration are standout soft skills for this role. These competencies are vital for developing innovative models that can process and interpret complex, multi-source data to drive impactful AI solutions.

What are some common challenges faced by professionals working in multimodal learning roles, and how can they be addressed?

Professionals in multimodal learning frequently encounter challenges related to integrating and aligning data from multiple sources, such as text, images, audio, or video. Ensuring data quality and consistency across modalities can be complex, and developing models that effectively combine heterogeneous information often requires advanced technical skills and innovative thinking. Collaboration with domain experts and other data scientists is key to overcoming these obstacles, as is staying up to date with the latest research and tools in machine learning. Regular team meetings and cross-disciplinary workshops can help foster a collaborative environment and promote knowledge sharing.

What is the difference between Multimodal Learning vs Data Scientist?

AspectMultimodal LearningData Scientist
Required CredentialsAdvanced degrees in AI, Machine Learning, or Computer ScienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, AI development teams, academiaBusiness, tech companies, analytics teams
Industry UsageAI research, multimedia applications, roboticsData analysis, predictive modeling, business insights

Multimodal Learning focuses on developing AI models that process and integrate multiple data types like images, text, and audio. Data Scientists analyze data to extract insights, build models, and support decision-making. While both roles involve data and algorithms, Multimodal Learning is specialized in AI model development for complex data integration, whereas Data Scientists work broadly across data analysis and interpretation.

What are popular job titles related to Multimodal Learning jobs in Leander, TX?

For Multimodal Learning jobs in Leander, TX, the most frequently searched job titles are:

What cities near Leander, TX are hiring for Multimodal Learning jobs?

Cities near Leander, TX with the most Multimodal Learning job openings:

Infographic showing various Multimodal Learning job openings in Leander, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $58,947 per year, or $28.3 per hour.

Social Science/Humanities Research Associate I.

The University of Texas at Austin

Austin, TX • On-site

$40K/yr

Full-time

Re-posted 12 days ago


University Of Texas at Austin rating

8.3

Company rating: 8.3 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

128th of 621 rated colleges and universities


Job description

Job Posting Title:
Social Science/Humanities Research Associate I.
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Hiring Department:
College of Liberal Arts
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Position Open To:
All Applicants
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Weekly Scheduled Hours:
40
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FLSA Status:
Non-Exempt from FLSA
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Earliest Start Date:
Immediately
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Position Duration:
Expected to Continue Until May 31, 2028
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Location:
UT MAIN CAMPUS
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Job Details:
General Notes
Lori Holt, a Professor of Psychology at UT-Austin and Principal Investigator of the project, is seeking a Research Associate to assist with laboratory management and coordination of studies. The Research Associate will collaborate with team members and work closely with Professor Holt to coordinate day-to-day lab operations and research. Data collection occurs online and in person.
This is a 2 year fixed-position.
Purpose
The primary research in the lab focuses on understanding the cognitive and neural bases of auditory processing, especially as it relates to speech, among adult participants. Under the direction of Professor Holt, the candidate will work on federally funded research to uncover the basis of listening behavior. Current projects focus on learning, selective attention, natural communication, and psychophysics. Laboratory studies include collecting multimodal behavioral data, eye tracking, computational modeling, and electroencephalography data.
Responsibilities
Responsibilities will vary day-to-day depending on the needs of the laboratory, for example:
  • Assisting the PI with training laboratory members and maintaining lab documentation.
  • Assisting with new experiment set-ups (hardware and software).
  • Collecting in-person data.
  • Summarizing data with supervision.
  • Drafting and editing research reports, with supervision.
  • Coordinating Laboratory meetings.
  • Searching and summarizing the literature.
  • Assisting with grant reporting, ethics approvals, financial reconciliation, and laboratory record keeping.
  • Coordinating, training and working with undergraduate research assistants.
  • Lending research support to laboratory team members.
  • Performs related duties as needed to advance the research project.

Required Qualifications
  • BA or BS in psychology, cognitive science, neuroscience or related field
  • Fluency in speaking and writing in English
  • Flexibility and an ability to learn quickly
  • Excellent interpersonal skills
  • Strong initiative in consistently and creatively meeting project goals
  • Strong written and oral communication skills
  • Ability to work independently as well as part of a scientific team
  • Curiosity and a willingness to learn new skills independently
  • Accuracy and attention to detail and high levels of organization

Relevant education and experience may be substituted as appropriate.
Preferred Qualifications
  • Prior research experience
  • Coding experience (Python, R, Matlab, e.g.)
  • Statistics training
  • Previous exposure to auditory cognitive neuroscience or a strong interest in perception, learning, cognition, or related fields

Salary Range
$40,000 annually
Working Conditions
The position will involve working in standard office environment, with the potential for repetitive use of keyboard at a workstation
Required Materials
  • Resume/CV
  • 3 work references with their contact information; at least one reference should be from a supervisor
  • Letter of interest

Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required 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 UT Jobs. If you are a current University employee, 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 before you apply. This information will be pulled in to your application. The application is one page and you will be prompted to upload your resume. In addition, you must respond to the application questions presented to upload any additional Required Materials (letter of interest, references, etc.) that were 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.
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 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.
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 documents 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.
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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:
  • E-Verify Poster (English and Spanish) [PDF]
  • Right to Work Poster (English) [PDF]
  • Right to Work Poster (Spanish) [PDF]

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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 HOP-3031.
The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.

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