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Internship Machine Learning Neuroscience Jobs in Waltham, MA

Neurable, INC

Machine Learning

Cambridge, MA · On-site

... neuroscience, enables people to control hardware and software in real-time with their brain via a ... We are currently looking for a Machine Learning Scientist/Researcher to join our team. We would ...

Neurable, INC

Machine Learning

Cambridge, MA · On-site

... neuroscience, enables people to control hardware and software in real-time with their brain via a ... We are currently looking for a Machine Learning Scientist/Researcher to join our team. We would ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA

$110K - $145K/yr

We are seeking a Machine Learning Analyst to join the growing data analytics and machine learning ... internships, undergraduate research or thesis, or substantial independent technical projects ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

We are seeking a Machine Learning Analyst to join the growing data analytics and machine learning ... internships, undergraduate research or thesis, or substantial independent technical projects ...

Crowe LLP

Machine Learning Intern

Boston, MA · On-site

$27 - $42/hr

DS interns will have a designated data scientist mentor and will spend the majority of their time working on a data science project overseen by that mentor. The expectation is that at the end of the ...

Capital One

Lead Machine Learning Engineer

Boston, MA

$111K - $146K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Boston, MA · On-site

$111K - $146K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

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Internship Machine Learning Neuroscience information

See Waltham, MA salary details

$27.5K

$45.9K

$94.9K

How much do internship machine learning neuroscience jobs pay per year?

As of Sep 7, 2026, the average yearly pay for internship machine learning neuroscience in Waltham, MA is $45,941.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,100.00 and $49,600.00 per year, depending on experience, location, and employer.

What is an internship in machine learning neuroscience?

An Internship in Machine Learning Neuroscience is a temporary position, often for students or recent graduates, that involves applying machine learning techniques to neuroscience research. Interns may work on projects such as analyzing brain imaging data, modeling neural networks, or developing algorithms to understand brain function. These internships provide hands-on experience in both computational methods and neuroscience concepts, helping interns build valuable skills for future academic or industry roles. Opportunities can be found in universities, research institutes, or technology companies with neuroscience divisions.

What types of projects do interns typically work on in a machine learning neuroscience internship?

Interns in Machine Learning Neuroscience often engage in projects that combine data analysis, algorithm development, and neuroscience research. This can include tasks such as preprocessing neural data, building and evaluating machine learning models to interpret brain signals, or developing tools for data visualization. Interns frequently collaborate with both data scientists and neuroscientists, gaining hands-on experience with real-world datasets and exposure to interdisciplinary research environments. These projects help interns build practical skills and contribute meaningful insights to ongoing research.

What are the key skills and qualifications needed to thrive as an internship machine learning neuroscience, and why are they important?

To thrive in an Internship Machine Learning Neuroscience role, you generally need a background in neuroscience, computer science, or a related field, along with a solid understanding of machine learning concepts. Experience with programming languages such as Python, libraries like TensorFlow or PyTorch, and familiarity with neuroimaging software are commonly required. Strong analytical thinking, problem-solving skills, and effective communication help you work collaboratively and adapt to complex research environments. These skills are essential for contributing meaningfully to interdisciplinary projects at the intersection of neuroscience and artificial intelligence.

What is the difference between Internship Machine Learning Neuroscience vs Internship Data Science?

AspectInternship Machine Learning NeuroscienceInternship Data Science
Required CredentialsBackground in neuroscience, machine learning, programmingBackground in statistics, programming, data analysis
Work EnvironmentResearch labs, healthcare, academia, tech companiesBusiness, tech firms, research institutions
Industry UsageNeuroscience research, AI development, healthcare techBusiness analytics, product development, consulting

Internship Machine Learning Neuroscience focuses on applying machine learning techniques to neuroscience data, often within research or healthcare settings. In contrast, Internship Data Science covers a broader range of data analysis across industries. Both roles require programming skills, but the focus and industry applications differ significantly.

Is machine learning used in neuroscience?

Machine learning is extensively used in neuroscience, including in roles like Internship Machine Learning Neuroscience, to analyze complex brain data, model neural activity, and develop brain-computer interfaces. Skills in data analysis, programming, and understanding neural systems are essential for these applications.

What are the most commonly searched types of Machine Learning Neuroscience jobs in Waltham, MA?

The most popular types of Machine Learning Neuroscience jobs in Waltham, MA are:

Internship Machine Learning Neuroscience jobs near you

Fellow in AI/ML for NeuroAI and Computational Neurobiology

Harvard University

Cambridge, MA • On-site

$54K - $73K/yr

Full-time

Re-posted 17 days ago

Harvard University rating

8.5

Company rating: 8.5 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

82nd of 631 rated colleges and universities

Job description

Position
Details
Title
Fellow in AI/ML for NeuroAI and Computational Neurobiology
School
Faculty of Arts and Sciences
Department/Area
Kempner Institute for the Study of Natural and Artificial Intelligence
Position Description
The Kempner Institute at Harvard University seeks early-career researchers to help shape the future of NeuroAI as Kempner AI Fellows. We are looking for candidates with strong foundations in modern machine learning and the ambition to build brain foundation models and other AI systems that advance our understanding of neural activity, brain circuits, and biologically grounded intelligence.
We seek candidates with strong technical preparation in modern AI/ML, a demonstrated record of research accomplishment, and an interest in contributing to ambitious research at the intersection of machine learning, neuroscience, and computational biology. This role centers on computational neurobiology and the use of modern AI/ML methods to model brain circuits and neural activity. In particular, fellows will help develop brain foundation models that predict patterns of neural activity from large-scale, multi-regional recordings.
We are especially interested in candidates with experience in computational neurobiology or neural data analysis, and expertise in one or more of the following areas:
  • foundation model training, evaluation, and adaptation
  • time-series modeling
  • transformers, autoencoders, and dynamical systems models
  • modeling brain circuits and neural activity from large-scale recordings
  • large-scale scientific applications of AI/ML, including in the life sciences

AI Fellows will work closely with one another and with Kempner faculty, researchers, and students on foundational machine learning and neuroscience-informed scientific applications. The position is particularly well-suited to candidates eager to apply their technical expertise in foundation models to important questions in neuroscience and biological intelligence.
Appointment Terms
  • Fellows will conduct research under the direction of a Kempner Institute investigator.
  • Fellows are appointed for a one-year term; reappointment may be possible for up to three consecutive years.
  • Due to the importance of in-person mentoring, this position is based on campus, full-time, at Harvard University. Remote work for this position is not possible.

Basic Qualifications
  • Bachelor's or master's degree in computer science, statistics, electrical engineering, applied mathematics, computational neuroscience, computational biology, neurobiology, physics, or a related quantitative field required by the expected start date
  • Strong technical background in modern AI/ML, including deep learning and hands-on experience with frameworks such as PyTorch or JAX
  • Demonstrated research productivity, including publications in venues such as ICML, ICLR, NeurIPS, COSYNE, CCN, or similar, and/or substantial open-source research contributions
  • Demonstrated experience implementing, training, evaluating, or fine-tuning modern machine learning models
  • Strong programming skills in Python and experience building and maintaining research code
  • Demonstrated ability to use modern AI-assisted and agentic coding tools effectively, such as Claude Code, Codex, or similar systems, in research and development workflows
  • Experience in computational neurobiology, neural data analysis, or modeling neural activity from large-scale recordings
  • Ability to work effectively in a collaborative research environment and communicate technical work clearly

Additional Qualifications
  • Experience with foundation model training, post-training, adaptation, or evaluation
  • Experience with time-series modeling
  • Experience with transformers, autoencoders, dynamical systems models, or related approaches for sequential or neural data
  • Experience modeling brain circuits and neural activity from large-scale, multi-regional recordings
  • Experience with large-scale datasets, distributed training, or high-performance computing environments
  • Expertise in neuroscience, biologically grounded intelligence, and scientific applications of AI/ML

Special Instructions
Please submit the following items in PDF format no later than 11:59pm EST Monday, June 1, 2026:
  1. CV.
  2. A research statement of no more than 2 pages describing your experience using modern AI/ML to model neural activity, brain circuits, or other neuroscience data. Please be specific about your individual contributions.
  3. References - 1-2 required
    • Please give the emails of up to 2 individuals who can describe your work and your potential for future discoveries.
    • Referees will be contacted to submit the letters directly to the Kempner Institute.
    • The application will not be considered complete until all letters have been received.
  4. Transcripts (Undergraduate and/or Master's)

Candidates selected for further consideration will be asked to submit a short video presentation reviewing their past work; additional details will be provided at that stage. Following review of the videos, a subset of candidates will be invited to interview with members of the selection committee via zoom.
Applications received after the deadline will be reviewed on a rolling basis if positions remain available.
We anticipate a start date of September 15, 2026.
Contact Information
Molly Marshall
Contact Email
Kempnerinstitute@harvard.edu
Salary Range
Expected annual salary is $54,600 for candidates holding a bachelor's degree and $60,060 for candidates holding a master's degree. Salary will be commensurate with qualifications and experience.
Minimum Number of References Required
1
Maximum Number of References Allowed
2
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