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Internship Machine Learning Neuroscience Jobs (NOW HIRING)

Tacit

Machine Learning Scientist

San Francisco, CA · On-site

$180K - $270K/yr

PhD in computer science, machine learning, computational neuroscience, or related fields (or equivalent industry experience). * Expertise in deep learning frameworks (e.g., PyTorch, TensorFlow) and ...

Jane Street

Machine Learning Researcher

New York, NY · On-site

You'll spend the bulk of your internship working closely with full-time machine learning researchers on projects drawn from their own work. You might conduct an end-to-end study of an unexplored ...

Jane Street

Machine Learning Researcher

New York, NY · On-site

You'll spend the bulk of your internship working closely with full-time machine learning researchers on projects drawn from their own work. You might conduct an end-to-end study of an unexplored ...

Neurable, INC

Machine Learning

Cambridge, MA

... 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 ...

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $180K/yr

Desired Qualifications * 2-8+ years of experience (including internships or research) in machine learning, reinforcement learning, or scientific computing-or a strong recent graduate with ...

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 ...

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Internship Machine Learning Neuroscience information

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$25.5K

$42.6K

$88K

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

As of Aug 17, 2026, the average yearly pay for internship machine learning neuroscience in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

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.

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 cities are hiring for Internship Machine Learning Neuroscience jobs?

Cities with the most Internship Machine Learning Neuroscience job openings:

What are the most commonly searched types of Machine Learning Neuroscience jobs?

The most popular types of Machine Learning Neuroscience jobs are:

What states have the most Internship Machine Learning Neuroscience jobs?

States with the most job openings for Internship Machine Learning Neuroscience jobs include:

Internship Machine Learning Neuroscience jobs near you

Machine Learning Scientist

Tacit

San Francisco, CA • On-site

$180K - $270K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 24 days ago

Job description

About Tacit
We are an early-stage, deep tech startup based in San Francisco, developing innovative hardware that rethinks human-computer interaction. We are backed by General Catalyst, Khosla Ventures, and Greylock Partners, with a founding team from Stanford, BrainGate, Oculus, and Tesla. While we can't reveal too much just yet, our team is tackling cutting-edge engineering challenges to bring revolutionary products to life.
About the role
As a Machine Learning Scientist, you will develop cutting-edge AI models to integrate and decode complex, multimodal data streams from our custom sensing hardware. You'll play a pivotal role in advancing our technology stack by building and optimizing models for real-time applications. This position spans foundational research in deep learning, hands-on model development, and applying algorithms to scale across diverse data sources and users.
Responsibilities:
  • Design and implement state-of-the-art machine learning algorithms for processing multimodal biosignals, including time series, spatial, and spectral data.
  • Build and optimize neural network architectures.
  • Develop and evaluate multimodal learning techniques to fuse information from multiple sensor modalities.
  • Iterate rapidly on model prototypes for real-time inference on custom hardware.
  • Create and maintain a robust evaluation framework for benchmarking model performance across datasets and participants.
  • Collaborate closely with a diverse team, including hardware engineers, neuroscientists, and product, to align models with user needs.

Requirements:
  • PhD in computer science, machine learning, computational neuroscience, or related fields (or equivalent industry experience).
  • Expertise in deep learning frameworks (e.g., PyTorch, TensorFlow) and fluency in Python.
  • Track record of publishing or deploying machine learning models in real-world systems.
  • Independent work ethic, flexibility, and resourcefulness.
  • Effective communication and collaboration skills.
  • Comfortable in fast moving startup environment, excited to build independently

Preferred Qualifications:
  • Familiarity with human-machine interaction systems such as automatic speech recognition or neural interfaces.
  • Hands-on experience with consumer wearables or custom hardware.
  • Knowledge of low-latency inference techniques and model optimization for edge devices.

Details:
  • This position is full time, onsite in San Francisco (SOMA)
  • Company size: 30-40 people

Compensation Range
$180,000 - $270,000/year
Benefits
  • Competitive equity package
  • Comprehensive medical, dental, and vision insurance
  • Unlimited PTO
  • Visa sponsorship
  • 4% 401k matching

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