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Deep Learning Research Jobs (NOW HIRING)

As a not-for-profit, we support patient care, research, teaching, and community service, striving ... Development and refinement of deep learning and other benchmark algorithms for predictive ...

We apply deep learning research to large scale neural datasets to decode internal thought directly. By advancing the frontier of neural decoding, we aim to unlock meaningful breakthroughs in human ...

In this role, you will conduct original research in areas such as deep learning, representation learning, generative modeling, optimization, and large-scale model architectures. You will collaborate ...

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Deep Learning Research information

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$21.5K

$183.1K

$401K

How much do deep learning research jobs pay per year?

As of Sep 9, 2026, the average yearly pay for deep learning research in the United States is $183,146.00, according to ZipRecruiter salary data. Most workers in this role earn between $136,000.00 and $212,000.00 per year, depending on experience, location, and employer.

What is deep learning research?

A Deep Learning Research job involves investigating and developing advanced machine learning techniques, particularly deep neural networks, to improve AI performance. Researchers design new models, optimize algorithms, and experiment with architectures to solve complex problems in areas like computer vision, natural language processing, and reinforcement learning. They often work in academia, industry, or research labs, publishing findings in conferences and collaborating with engineers to integrate advancements into real-world applications.

What are the key skills and qualifications needed to thrive in deep learning research?

To thrive in Deep Learning Research, you need a strong background in mathematics, computer science, and machine learning principles, often backed by advanced degrees such as an MSc or PhD. Experience with programming languages like Python, proficiency in frameworks such as TensorFlow or PyTorch, and familiarity with high-performance computing resources are highly valuable. Strong analytical thinking, problem-solving skills, and the ability to communicate complex ideas effectively are essential soft skills. These capabilities ensure you can design, implement, and present innovative deep learning solutions that advance research and address real-world challenges.

What are some common challenges faced by professionals working in deep learning research?

Professionals in Deep Learning Research often encounter challenges such as working with large and complex datasets, ensuring model interpretability, and managing limited computational resources. Staying up-to-date with the rapidly evolving literature and adapting to new techniques or frameworks is also crucial. Additionally, translating research results into practical, scalable applications and collaborating with cross-functional teams can be both demanding and rewarding. Overcoming these challenges requires a combination of technical expertise, creativity, and strong communication skills, making each day dynamic and intellectually stimulating.

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What cities are hiring for Deep Learning Research jobs?

Cities with the most Deep Learning Research job openings:

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

The most popular types of Deep Learning Research jobs are:

What states have the most Deep Learning Research jobs?

States with the most job openings for Deep Learning Research jobs include:

What are popular job titles related to Deep Learning Research jobs?

For Deep Learning Research jobs, the most frequently searched job titles are:

Infographic showing various Deep Learning Research job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $183,146 per year, or $88.1 per hour.

Research Fellow - Deep Learning

Boston, MA • On-site

$70K - $71K/yr

Full-time

Re-posted 27 days ago


Brigham and Women's Hospital rating

8.1

Company rating: 8.1 out of 10

Based on 101 frontline employees who took The Breakroom Quiz

119th of 1,066 rated hospitals


Job description

Site: Massachusetts Eye and Ear Infirmary
Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.
Job Summary
We have an open position for a computer science/machine-learning postdoctoral fellow to work on machine-learning algorithms for automatic diagnosis of dystonia, prediction of the risk for dystonia development, and the efficacy of treatment outcomes. This work will be directly related to the extension of our recently developed DystoniaNet platform and will include brain MRI datasets from patients with dystonia, other movement disorders, and healthy individuals.
The postdoctoral fellow will be part of a multidisciplinary team of neuroscientists, neurologists, laryngologists, and geneticists at Mass Eye and Ear and Mass General Hospital and work at the intersection on the development, testing and implement of DystoniaNet in the clinical setting. This position is best suited for an individual with a broad computer science background interested in understanding and examining critical clinical problems and developing research solutions for their translation to healthcare. The fellow will be highly competitive to pursue future opportunities in either academia or industry (pharma and biotech).
Qualifications
Postdoctoral Fellow in Deep Learning
We have an open position for a computer science/machine-learning postdoctoral fellow to work on machine-learning algorithms for automatic diagnosis of dystonia, prediction of the risk for dystonia development, and the efficacy of treatment outcomes. This work will be directly related to the extension of our recently developed DystoniaNet platform and will include brain MRI datasets from patients with dystonia, other movement disorders, and healthy individuals.
The postdoctoral fellow will be part of a multidisciplinary team of neuroscientists, neurologists, laryngologists, and geneticists at Mass Eye and Ear and Mass General Hospital and work at the intersection on the development, testing and implement of DystoniaNet in the clinical setting. This position is best suited for an individual with a broad computer science background interested in understanding and examining critical clinical problems and developing research solutions for their translation to healthcare. The fellow will be highly competitive to pursue future opportunities in either academia or industry (pharma and biotech).
Responsibilities include but may not be limited to
  • Experimental data collection and processing
  • Development and refinement of deep learning and other benchmark algorithms for predictive classification of dystonia and other related disorders
  • Clinical translation and implementation of the developed algorithms and interactions with clinicians for their testing
  • Establishment of new and fostering of existing collaborations
  • Participation in the regulatory aspects of clinical translation and patenting
  • Presentation of the results at the scientific meetings and publication of journal articles
  • Mentoring junior staff

Qualifications and Skills
  • PhD or an equivalent degree in computer science, neuroscience, biomedical engineering, or related fields
  • Broad proficiency and experience with supervised and unsupervised machine-learning methods, expertise in building neural network architectures
  • Experience with neuroimaging data processing
  • Advanced programming skills (Python and/or Matlab), including deep learning packages (e.g., TensorFlow or Keras)
  • Knowledge and experience with cloud-based computational platforms (e.g., AWS)
  • Excellent verbal and written communication skills
  • Strong publication record and academic credentials
  • Ability to work effectively both independently and in collaboration with multiple investigators

Pay Range: $70,000.00 - $71,750.00/Annual
Additional Job Details (if applicable)
Remote Type
Onsite
Work Location
243-245 Charles Street
Scheduled Weekly Hours
40
Employee Type
Regular
Work Shift
Day (United States of America)
EEO Statement:
5110 Massachusetts Eye and Ear Infirmary is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veteran's Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at (857)-282-7642.
Mass General Brigham Competency Framework
At Mass General Brigham, our competency framework defines what effective leadership "looks like" by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.

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