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Research Assistant Deep Learning Jobs in Washington

Howard University

Research Assistant

Washington, DC · On-site

$21 - $31/hr

Research Assistant will assist with user testing and user centered design of biometric technologies ... in machine learning and data science; advanced degrees may offset experience requirements ...

Howard University

Research Assistant

Washington, DC · On-site

$20/hr

The position is designed to integrate academic learning with practical research experience ... PRINCIPAL ACCOUNTABILITIES: * Assist in the design and execution of research experiments, surveys ...

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Research Assistant Deep Learning information

What is the difference between Research Assistant Deep Learning vs Research Assistant Machine Learning?

AspectResearch Assistant Deep LearningResearch Assistant Machine Learning
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related fields; knowledge of neural networksBachelor's or Master's in Computer Science, Data Science, or related fields; foundational ML knowledge
Work EnvironmentResearch labs, universities, tech companies focusing on AI and neural networksResearch labs, universities, tech companies working on various ML algorithms
Employer & Industry UsageAI research, deep learning projects, neural network developmentGeneral machine learning applications, data analysis, predictive modeling

Research Assistant Deep Learning specializes in neural networks and AI-focused projects, while Research Assistant Machine Learning covers a broader range of algorithms and data analysis tasks. Both roles require similar educational backgrounds but differ in technical focus and application areas.

What is a research assistant deep learning?

Research Assistant Deep Learning jobs involve supporting research projects focused on artificial intelligence, specifically within the field of deep learning. These roles typically require assisting with data collection, preprocessing, running machine learning experiments, and analyzing results. Research assistants may also help with literature reviews, code development, and documentation. The position is often found in academic, industry, or research lab settings, and usually requires a solid foundation in programming, mathematics, and neural network concepts.

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

To thrive as a Research Assistant in Deep Learning, you need a strong background in machine learning, programming (especially Python), and a relevant degree in computer science or a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, as well as experience with data preprocessing and GPU computing, are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills and qualities are essential for efficiently developing, testing, and improving advanced machine learning models in a fast-evolving field.

What does a research assistant deep learning do?

As a Research Assistant in Deep Learning, you can expect to work closely with research scientists and engineers to design, implement, and evaluate novel deep learning models. Typical daily tasks include data preprocessing, running experiments, analyzing results, and contributing to academic papers or presentations. You may also assist in developing codebases, conducting literature reviews, and collaborating with team members to solve technical challenges. The work environment is often collaborative and fast-paced, with opportunities to learn from experts and contribute to cutting-edge research projects.
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Research Assistant Deep Learning jobs near you
Infographic showing various Research Assistant Deep Learning job openings in Washington 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, 3% Hybrid, and 10% Remote job distribution.

Deep Learning Expert/Developer (On-site)

Ripple Effect

Bethesda, MD • On-site

$90K - $103K/yr

Full-time

Posted 16 days ago

Job description

General Information 
  • Job Code: SHR-BI-03
  • Location: NIH Campus onsite, with ad-hoc telework
  • Employee Type: Exempt, Full-Time Regular
  • Clearance: Must be able to work in the U.S. without employer sponsorship
  • Salary Range: $90,267-$103,808  (how we pay and promote)  
Position Overview 

Are you passionate about turning complex data into meaningful insights? As a Deep Learning Developer on the Ripple Effect team, you will play a pivotal role in shaping our success in this important role with the NIH! Your work will directly impact the Lister Hill Center's work. This position involves applying deep learning techniques to biomedical images and clinical data for clinical decision-making and prediction. The role focuses on the development of tools for retinal disease detection, severity classification, disease progression prediction, and more. The ideal candidate will have a strong background in deep learning, particularly for medical image analysis, and experience with high-performance computing environments.

While not an exhaustive list, the key duties for the position include: 

    • Develop deep learning models to support clinical decision-making for retinal diseases using retinal images, genomic data, and clinical records.
    • Develop algorithms for disease detection, severity classification, and longitudinal progression prediction, focusing on retinal diseases as well as other patient data.
    • Build and optimize deep learning tools for deployment on Android/iOS/Web-based platforms.
    • Other related duties as assigned.

Requirements

Minimum Qualifications  
  • Master's degree
  • 5 or more years of experience in image analysis, machine learning, and deep learning
Basic Requirements  
    • Proven experience writing manuscripts or papers for journals and conferences.
    • Extensive experience with medical image processing, data analysis, and classification techniques.
    • Expertise in developing custom deep learning workflows, including visualizing activations.
    • Strong understanding of machine learning techniques, including Support Vector Machines (SVM), Multilayer Perceptron (MLP), and Convolutional Neural Networks (CNNs).
    • Proficiency in Decision Tree algorithms such as Random Forest, XGBoost, and LightGBM.
    • Experience in statistical analysis of experimental results.
    • Familiarity with Linux and Windows environments.
    • Hands-on experience with high-performance GPU clusters and multi-GPU setups for deep learning tasks.
    • Expertise in programming with Python, Keras, and PyTorch.
    • Experience in developing Android, iOS, or web applications.
    • Must reside within a commutable distance from the NIH main campus in Bethesda, MD, and be willing to report on site on a daily basis for this role.

Skills That Set You Apart 

  • PhD in computer science, computer engineering, or relevant field
  • Familiarity with Linux and Windows environments.
  • Intermediate experience with (levels 03+) Microsoft Office productivity software and collaboration tools such as Microsoft Teams and SharePoint. 
  • Intermediate experience with workplace AI tools, including their limitations and risks, and how they can be applied to support project management tasks. 

About Ripple Effect 

Ripple Effect is a woman-owned, 200-person company of communicators, scientists, researchers, and analysts. Established in 2003, and named as one of the "Best and Brightest Companies to Work For" in 2024 and 2025 by the NABR, Ripple Effect has earned acclaim for delivering unparalleled consulting services and top-tier talent across federal, private, and non-profit sectors. 

Benefits

At Ripple Effect, we reward our employees for their contributions to our mission. Our comprehensive total rewards package includes competitive pay, exceptional benefits, and a range of programs that support your work/life balance and personalized preferences.  

Learn more about our benefits and culture here. 

Apply