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How much do deep learning research intern jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for deep learning research intern in Texas is $15.75, according to ZipRecruiter salary data. Most workers in this role earn between $13.22 and $17.64 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a deep learning research intern?

To thrive as a Deep Learning Research Intern, you need a strong grasp of machine learning fundamentals, programming skills (especially in Python), and a background in mathematics or computer science, often supported by relevant coursework or research experience. Familiarity with deep learning frameworks such as TensorFlow or PyTorch and proficiency in using data processing and visualization tools are typically expected. Creativity, problem-solving abilities, and effective communication help interns contribute novel ideas and collaborate within research teams. These skills are vital for developing, testing, and presenting cutting-edge AI models and solutions in a fast-evolving field.

What does a deep learning research intern do?

A Deep Learning Research Intern assists in the development and experimentation of machine learning models, particularly neural networks, to solve complex problems in fields like computer vision, natural language processing, or robotics. They typically work under the guidance of experienced researchers, contributing to tasks such as data preprocessing, model training, and result analysis. Interns may also help implement and optimize algorithms, read and summarize research papers, and prepare reports or presentations on their findings. This role provides hands-on experience with state-of-the-art AI technologies and research methodologies.

What are some common challenges faced by deep learning research interns, and how can they overcome them?

Deep Learning Research Interns often encounter challenges such as managing complex datasets, tuning neural network architectures, and keeping up with the latest research developments. It's common to spend significant time troubleshooting code or optimizing models for better performance. Collaborating closely with mentors and team members, actively participating in research discussions, and consistently reading recent papers can help interns overcome these hurdles. Utilizing open-source tools and frameworks, along with clear documentation practices, also streamlines the research process.

What are the most commonly searched types of Deep Learning Research jobs in Texas?

The most popular types of Deep Learning Research jobs in Texas are:

What cities in Texas are hiring for Deep Learning Research Intern jobs?

Cities in Texas with the most Deep Learning Research Intern job openings:

Deep Learning Research Intern jobs near you

Research Intern - Radiation Oncology - Research

MD Anderson Cancer Center

Houston, TX • On-site

Internship

Re-posted 6 days ago

MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 170 frontline employees who took The Breakroom Quiz

23rd of 887 rated healthcare providers

Job description

The Research Intern position is a trainee-level position designed for recent graduates seeking hands-on experience in clinical and translational cancer research. The intern will work under the guidance of a faculty mentor and research team to support ongoing studies while developing foundational skills in oncology research. This role provides direct exposure to the research process, including study design, data collection, data analysis, and dissemination of findings. The intern is expected to actively contribute to research activities while participating in structured training and educational programs.
Key Responsibilities
• Assist with literature reviews to support research projects
• Participate in data collection, data entry, and data management
• Support data analysis and interpretation under supervision
• Contribute to research deliverables, including abstracts, presentations, and manuscripts
• Attend and participate in research meetings, seminars, and educational sessions
• Collaborate with faculty mentors and research teams on assigned projects
• Ensure compliance with institutional research protocols and IRB requirements
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
By the end of the appointment, the intern will:
• Understand the fundamentals of radiation oncology research and clinical studies
• Describe a research project, including objectives, methodology, and endpoints
• Demonstrate basic skills in data analysis, scientific writing, and literature evaluation
• Present research findings through a poster, presentation, or written report
ELIGIBILITY REQUIREMENTS
Required:
• Bachelor's or Master's degree (recently obtained, typically within one year)
• Prior research experience
• Strong organizational, analytical, and communication skills
Preferred:
• Interest in oncology, clinical research, or academic medicine
• Experience with data analysis or scientific writing
POSITION INFORMATION
Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

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